Data science is an essential part of any industry today, given the massive amounts of data that are produced. Data science is one of the most debated topics in the industries these days. With its growing popularity, the jobs related to data science are also growing. Here are the latest data science jobs one can apply for this weekend.

Data scientist at Hire Digital

Location: Kolkata, West Bengal

Responsibilities

• Design and implement machine learning models.
• Work closely with data engineers to set up data warehouses and pipelines that will feed into predictive or analytical models.
• Design and implement machine learning pipelines taking into account costs, accuracy, and technical risks.
• Work closely with cross-functional teams to understand business requirements and make appropriate technical recommendations.
• Identify opportunities from in-house big data to improve business performance (data mining).

Requirements

• 5-7 years of experience in applying AI/ML and data science techniques to solve business problems.
• Degree in Computer Science.
• Any software engineering and product shipping experience is a plus.
• Background in the Consumer-Packaged Goods industry is a plus.
• Good communication, analytical and conceptual skills.
• Self-driven, a hunger for learning, and a penchant for teamwork.

Data scientist at PayPal

Location: Chennai, Tamil Nadu

Primary responsibilities:

• Conceive, design, and monitor fraud risk management strategies to manage fraud losses and improve business profitability for consumer lending products
• Identify opportunities and gaps within the current portfolio of PayPal’s Fraud Risk controls, including continuously evolving fraud trends
• Formulate & propose solutions to ensure optimal balance between user experience, business enablement, operational expense, and loss exposure
• Communicate concise and actionable business strategies and present new strategy recommendations to senior management for approval
• Monitor performance of existing & new solutions and optimize to ensure desired results
• Work closely with partners in Risk Platform, Data Sciences, Operations, Product Management, Legal & Compliance, and other teams to formulate and execute fraud risk solutions
• Collaborate with external partners, including external credit/banking partners and data vendors

Education & Required Skills:

• Bachelor’s degree in Mathematics, Statistics, Operations Research, Finance, Economics or related quantitative discipline
• 2-5 years proven credit or fraud risk analytics experience or equivalent
• Must be an intuitive, organized analytical thinker, with the ability to perform detailed analysis
• Proficiency in SQL and Excel. Proficiency in at least one statistical analysis tool: SAS / R / Python
• Strong written, oral, and interpersonal skills a must including the ability to explain and/or present analysis
• Ability to contribute to strategic discussions and represent Risk in cross-functional meetings
• Ability to manage a large, diverse set of to-dos – prioritize, stay on top of multiple workstreams, monitor progress
• Ability to work with leadership & stakeholders to define project scope and direction, driving large pieces of the work independently
• Experience working with cross-functional, geographically distributed teams, managing by influence is a plus.

Data Analyst at Uber

Location: Hyderabad, Telangana

The company is looking for a skilled Data Analyst to join their FinTech – Data Analytics team at Uber, Hyderabad to support their downstream financial systems. In this role, the employee will get an incredible opportunity to leverage analytics and science to get insights from financial data, help develop their financial reporting systems, detect anomalies in data, and streamline reporting of various financial metrics. The company will work closely with senior leaders in Finance, Product, Data Science, Engineering, and other stakeholders on fast-moving, high-stakes problems. A deep analytical passion and the ability to execute on key business priorities is a must for this role (financial knowledge is not expected to apply for this role but is a plus). Their performance is measured by the insights the employee gives, the effectiveness of communication, and the initiative to drive ideas and implement them into action.

Data Scientist at Volumetree

Location: Chandigarh

Responsibilities

• Identify valuable data sources and automate collection processes
• Undertake to preprocess of structured and unstructured data
• Analyze large amounts of information to discover trends and patterns
• Build predictive models and machine-learning algorithms
• Present information using data visualization techniques
• Propose solutions and strategies to business challenges
• Collaborate with engineering and product development teams

Requirements

• Can work independently
• Proven experience as a Data Scientist or Data Analyst
• Knowledge of SQL Python and ML
• Experience in data mining
• Understanding of machine-learning and operations research
• Knowledge of R, SQL, and Python; familiarity with Scala, Java, or C++ is an asset
• Experience using business intelligence tools (e.g., Tableau) and data frameworks (e.g., Hadoop)
• Analytical mind and business acumen
• Strong math skills (e.g., statistics, algebra)
• Problem-solving aptitude
• Excellent communication and presentation skills
• BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or another quantitative field is preferred
• Understand business requirement
• KPI identification

Data Engineer at Fortunefootprints.com

Location: Bengaluru, Karnataka

Responsibilities:

• Design and implement the data processing pipelines for different kinds of data sources, formats, and content for the Near Platform. Working with huge Data Lakes, Data Warehouse and Data Marts are part of this challenging role.
• Design and develop solutions that are scalable, generic, and reusable.
• Responsible for collecting, storing, processing, and analyzing huge sets of data that is coming from different sources.
• Develop techniques to analyze and enhance both structured/unstructured data and work with big data tools and frameworks.
• Collaborate closely with Data Scientists and Business Analysts to understand data and functional requirements.
• Design, build and support existing data pipelines to standardize, clean, and ingest data.
• Participate in product design and development activities supporting Near’s suite of products.
• Liaise with various stakeholders across teams to understand business requirements.

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Along with the increasing demand for decision-making, the data science jobs to apply also grows

Data scientists are one of the most sought-after roles in the corporate world. As organizations with enormous data and the right data science talents seek more meaningful outputs, executives believe that it can drive more value and enrich their company’s stance. This has drastically surged the need for experts who can gather, study, and understand data to make business decisions. As a result, the demand for data scientists continues to grow even as the overall job market is in jeopardy. Many top companies are opening the door for data science jobs, and are willing to pay high salaries, with other benefits included. But along with the demand, the expectations for data science jobs to apply also grow. The title ‘data scientists’ may soon become obsolete as new technologies change the responsibilities of the profession. Recent data science jobs to apply also demands the candidates be technological mature and bring profit to the company. In this article, Analytics Insight has listed the top data science jobs to apply for this week, especially for aspirants.

• DATA SCIENCE ROUND-UP: BEST ARTICLES ON ANALYTICS INSIGHT
• JOB ALERT: TOP DATA SCIENCE JOBS TO APPLY FOR THIS WEEKEND
• TOP GOVERNMENT DATA SCIENCE JOBS IN INDIA: GET RECRUITED TODAY

Top Data Science Jobs to Apply for This Week

Senior Data Scientists at Flipkart

Location: Bengaluru, India

About the company: Flipkart Private Limited, is an Indian e-commerce company established in 2007. Flipkart started with a primary focus on online book sales and soon expanded to lifestyle products, electronics, home essentials, and even groceries.

Roles and responsibilities: As a Senior Data Scientist at Flipkart, the candidate is expected to drive research and development of various machine learning and statistical models, keeping business goals and product planning at the front. He/she should be able to communicate and collaborate with multiple stakeholders representing various teams. They should understand business and product needs and use advanced modelling techniques to provide fashion to the trends. The candidate should develop research and hypothesis on problem statements around ongoing work to provide additional value to the organization.

Qualifications

• The candidate should hold a B.Tech degree in Computer Science or Statistics.
• He/she is mandated to have over 8 years of professional experience through publications or deployed solutions or projects.
• They should have a deep understanding of applied statistical analysis and predictive modelling is desired.
• The candidate should have standard proficiency in Python or R.

Senior Data Scientist – Adv ML at Optum Global Solutions

Location: Noida, India

About the company: Optum Global Solutions, is a healthcare solution unit of UnitedHealth Group. The company’s deep expertise, advanced analytics, and innovative technology help its customers drive sustainable health economics and more personalized care.

Roles and responsibilities: As a data scientist at Optum, the candidate is expected to conduct and manage outcomes of various studies that include analyzing, reviewing, forecasting, trending, and presenting information for operational and business planning. He/she should support short and long term operational strategies and business activities by developing, enhancing, and maintaining operational information and models. Their primary responsibilities include owning the delivery of projects by working closely with cross-functional data science, data engineering, and project management teams in the role of a lead.

Qualifications

• The candidate should have at least six years of professional experience in the data science field.
• He/she should also have extraordinary skills to solve real-world problems using advanced machine learning techniques.
• They should hold strong theoretical and practical knowledge of some of the most machine learning techniques like Random Forest, Support Vector, Machine, Gradient Boosting Machine, XGBoost, etc.
• The candidate should have a strong theoretical and practical knowledge of deep learning techniques.

Data Scientist at HCL

Location: Noida, Chennai- India

About the company: HCL Technologies, is a leading global IT services company that helps global enterprises re-imagine and transform their businesses through digital technology transformation. The company is primarily engaged in providing a range of software services, business process outsourcing, and infrastructure service.

Roles and responsibilities: The Senior Data Scientists, should perform advanced analysis and create machine learning models for various industries. He/she should work closely with the customer, subject matter experts, and business developers. For each project, the candidate should thoroughly go through the domain and the customers to identify the customer’s data and analytic needs and then visualize an end-to-end analytic solution.

Qualifications

• The candidate should have a Master’s or PhD degree in Math or computer science, or any quantitative field with additional experience.
• He/she should be an expert in applying machine learning algorithms for anomaly detections, regressions, classifications, time-series forecasts, etc.
• They should have good scripting skills in Python or R.
• Experience in image analysis, optimizations, and logistics are also required.

Data Scientist: Advanced Analytics at IBM

Location: Mumbai, India

About the company: IBM, also known as International Business Machines Corporation, is an American global consulting and technology conglomerate. It builds and advertises computer hardware and software, and provides hosting, infrastructure, and consulting facilities in fields that range from nanotechnology to mainframe computers.

Roles and responsibilities: As a Data Scientist: Advanced Analytics at IBM, the candidate is expected to transform the company’s client data into tangible business value by analyzing information, communicating outcomes, and collaborating on product development. He/she should work with the IBM Q Start team on active exploratory research engagement to prepare for future use case commercialization within a specific industry. They should engage and educate client data science teams to define promising areas of quantum explosion.

Qualifications

• The candidate should hold a PhD or Masters degree in STEM-related fields with knowledge in quantum computing.
• He/she should have five years of data engineering or data science experience.
• They should have proficiency in the classical approach to machines and linear algebra, including support vector machine (SVM) for linear categorization and singular value decomposition (SVD) to reduce the dimensionality of data.

Data Scientists and Engineers at Pfizer Limited

Location: Chennai, India

About the company: Pfizer, is a research-based global biopharmaceutical company that is engaged in the discovery, deployment, manufacturing, marketing, sales, and distribution of biopharmaceutical products. Its global portfolio includes medicines and vaccines.

Roles and responsibilities: The data scientists or engineers working at Pfizer is expected to provide expert advanced modelling and data analytics support to all teams in the manufacturing intelligence organizations and support of project execution at PGS manufacturing sites. He/she should work on supporting the development, testing, deployment, and qualification of process soft sensor models. They should stay abreast of industry 4.0 trends and development in artificial intelligence, machine learning, and work with other MI teams to pilot new advances to drive value for PGS.

Qualifications

• The candidate should have a relevant degree and background in Engineering, Mathematics, Statistics, Physics, Chemistry, Computer Science, or a related technical field with a strong focus on advanced analytics.
• He/she should have data analytics or modelling experience with domain expertise and industrial exposure.
• They should also have data science, ML, and AI experience including Scikit Learn, TensorFlow, and PyTorch libraries.

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Top data science jobs one should apply this weekend

Data science deals with the structuration, of scattered data and analyses them by using several types of tools and make data analysis models. Almost every organization is appointing data scientists at present to get better business value. The following are the latest data science jobs one can apply for this weekend.

Data Scientist at Cognizant

Location: Chennai, Tamil Nadu

Key Responsibilities

• Discover the information hidden in structured & unstructured data by applying data mining techniques, doing statistical analysis, and building high-quality prediction systems
• Evaluating business problems for suitability & feasibility of a predictive solution
• Evaluating & identifying the right machine learning and data science techniques & toolsets to address a variety of predictive analytics problems
• An individual contributor as well as a guide to the fellow team members in the discovery, design, and development of analytical models
• Working with functional & technical teams in the development, pilot & optimization of tools and models using machine learning & Natural Language Processing

Qualifications & Skills

• Advanced degree in statistics, computer science, machine learning, or related fields such as econometrics
• Professional experience in software engineering, with a good understanding of the Information Technology industry
• Experience in data mining (structured/unstructured data) & machine learning experience, with a proven ability to design and develop solutions across ML landscape (supervised, unsupervised, semi-supervised, etc.)

Data Science ML Consultant at Accenture

Location: Bengaluru, Karnataka

Responsibilities

• Data Manipulation & Hardcore passion for -Programming – Python & R
• ETL fundamentals
• Visual Story Telling with Data Visualization – R Shiny / Tableau / Power BI / Spotfire / BO
• Advanced Excel including VBA and PowerPoint skills

Education

• Master’s Degree (Statistics / Econometrics / Economics / Mathematics / Actuarials) or other relevant streams
• E / B. Tech. / M. Tech – proven track of passion for Data Science
• Premier Research Focused Institutes – IIT’s / REC’s / TISS / DSE / IISC etc.

Soft Skills

• Relevant Certifications in Programming & data science
• Excellent written and oral communication skills with the ability to clearly communicate ideas and results to non-technical business people
• You are laser-focused on delivering outcomes with speed and agility
• You are self-driven and thrive in ambiguity

Data Analyst at Amazon

Location: Bengaluru, Karnataka

Basic Qualifications

• Bachelor’s degree in Computer Science, Engineering, Operations Research, Math, or related discipline.
• Minimum 2+ years of experience as an Analyst role preferred.
• Highly proficient in Microsoft Office and Windows-based applications.
• SQL Knowledge and Hands-on experience are a must.
• Demonstrated Analytical ability, results-oriented environment with external customer interaction.
• Excellent written and verbal communication and presentation skills and the ability to express thoughts logically and succinctly.
• Entrepreneurial drive and demonstrated ability to achieve stretch goals in an innovative and fast-paced environment.

Preferred Qualifications

• Experience with E-Commerce, Retail, and Business Analytics would be an advantage.
• Understanding of data warehousing, data modeling concept, and building new DW tables
• Advanced SQL skills, fluent in R and/or Python, advanced Microsoft Office skills, particularly Excel and analytical platforms

Executive-Data Scientist at NielsenIQ

Location: Greater Vadodara Area

GDDC is responsible for all Design related activities in Data science. GDDC is responsible for setting up the base of any product like retail index, E-comm, Cash & Carry, Scan track service (new/existing). They work closely with all the stakeholders to understand the client requirements & provide recommendations/suggestions to best build up the product which balances expectations from both the client and methodological requirements. The GDDC team is responsible for processes starting from scope definition to panel sample design which would include processes like Sample design, extrapolation…

Data Scientist at PayPal

Location: Chennai, Tamil Nadu

Responsibilities

• Partner with stakeholders (Product, Engineering, Design) on SMB products to build world-class products and experiences
• Identify key metrics, conduct rigorous explorative data analysis, and build business cases that drive decision-making and product prioritization.
• Synthesizing large volumes of data with attention to granular details and present findings and recommendations to senior-level stakeholders
• Recommend A/B testing framework and measure the impact of product initiatives in an unbiased way.
• Drive automation of the repetitive processes, and build self-serve tools (eg: Tableau Dashboards) to empower product stakeholders

Requirements:

• The data-driven mindset with a degree in any quantitative discipline such as Engineering, Computer Science, Economics, Statistics or Mathematics
• 5+ of experience analyzing large, multi-dimensional data sets and synthesizing insights into actionable solutions.
• Fluent in SQL, Excel, and visualization tools such as Tableau or Qlikview; experience with a statistical programming language like R or Python preferred
• Strong communication skills, both written and verbal, to influence cross-functional teams
• Prior work experience in a product analytics space would be highly valued.

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Data science jobs combine computer science, statistics, and mathematics. They analyze, process, and model data then interpret the results to create actionable plans for companies and other organizations. Data scientists are analytical experts who utilize their skills in both technology and social science to find trends and manage data. They use industry knowledge, contextual understanding, skepticism of existing assumptions – to uncover solutions to business challenges. A data scientist’s work typically involves making sense of messy, unstructured data, from sources such as smart devices, social media feeds, and emails that don’t neatly fit into a database.

Data Scientist at PhonePe

Location: Bengaluru, Karnataka

About the company

PhonePe is India’s leading digital payments platform with over 280 million registered users. Using PhonePe, users can send and receive money, recharge mobile, DTH, data cards, pay at stores, make utility payments, buy gold, and make investments. PhonePe went live for customers in August 2016 and was the first non-banking UPI app and offered money transfer to individuals and merchants, recharges, and bill payments to begin with.

Responsibilities

The company is looking for senior data scientists who will work on applications related to financial services. They will work in a dynamic environment, and with cross-functional teams to assist those teams in every possible manner to ensure that our products help our users derive the most value. They will be expected to work with product, business, & engineering teams to help them understand what data science can do for them and set the right expectations, to analyze large volumes of data, and implement and deploy solutions as necessary. They should be able to clearly communicate results and recommendations to various stakeholders, They would need to evaluate the effectiveness of the solutions and improve upon them in a continuous manner. The company expects them to have a mix of a strong technical background, the ability to understand the business implications of their work, and the ability to empathize with our users and work towards helping PhonePe give them the best experience, and help and mentor junior members to become better data scientists.

Qualifications

• A Bachelor’s or higher degree in a quantitative discipline (computer science, statistics,
  engineering, applied mathematics)
• 6 – 7 years relevant work experience with a Bachelor’s degree, or 3-4 years relevant
  experience with a Master’s degree
• Specific technical skills include
• Expertise in Java, Python, R, shell scripting languages.
• Expertise in querying relational, non-relational, graph databases.
• Ability to clearly communicate and work with people of different backgrounds.
• Experience in big data technologies (Spark, MapReduce, Pig, Hive)
• Experience using machine learning (structured, text, video data) libraries
  (preferably in Python), deep learning (Tensorflow, PyTorch)
• Experience using visualization libraries
• Good to have: Hands-on experience with source control and deployment tools (Git,
  Jenkins, etc.)

Data Science Consultant at Wipro Limited

Location: Bengaluru, Karnataka

About the Company

Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading global information technology, consulting, and business process services company. They harness the power of cognitive computing, hyper-automation, robotics, cloud, analytics, and emerging technologies to help our clients adapt to the digital world and make them successful. A company recognized globally for its comprehensive portfolio of services, a strong commitment to sustainability, and good corporate citizenship, they have over 190,000 dedicated employees serving clients across six continents. Together, they discover ideas and connect the dots to build a better and bold new future.

Skills

As a consultant, the employees should have in-depth knowledge in any one technological or industry practice / functional area and an overview of 2-3 other areas. They should handle solution definition/ fitment for a small-sized project with medium complexity and should be able to build a custom Function Module with medium complexity program logic.

Data Scientist at Winfort

Location: Bangalore, Karnataka

Responsibility

• Develop Artificial intelligence solutions for client’s business problems to drive business outcome
• Develop data platforms to support analytical and AI/ML solutions
• Develop end-to-end integrated applications for operationalizing AI/ML models and Insights
• Develop impactful presentations to convey insights to a technical and non-technical audience
• Contribute to internal innovation development charted by leveraging
• Contribute to internal competency building initiatives on Analytics and AI / ML areas
• Support consulting and sales team in relevant opportunities

Skills & Experience

• Master’s in Business Administration / Engineering / Statistics / Economics / Operations Research / Computer Science / Data Science
• Experience in developing Artificial Intelligence applications leveraging Statistical / Machine Learning / Deep learning methodologies
• Data Visualization (technology agnostic)
• SQL, R or Python, Hive, Spark,

Associate Data Scientist at Shell

Location: Chennai, Tamil Nadu

Job Description:

• This position is part of Finance & Data Operations, Data Science team handling Contracting and Procurement (CP) portfolio, which delivers tangible value to Shell’s Supply Chain business through advanced analytical/Data Science projects
• The individual should demonstrate the skills and ability to take on advanced analytics projects, develop analytical solutions by collaborating with the business stakeholders/partners working across a range of technologies and tools
• The individual should design and articulate the data science solution relevant to Shell’s Supply Chain problems/opportunities in business-friendly language and explain the workings of the model for business adoption
• The ideal candidate should have a strong background in quantitative skills (like statistics, mathematics, advanced computing, machine learning) and should have applied those skills in solving real-time problems across different businesses/functions
• The candidate should provide support to the Team Lead in managing and executing projects.

Functional Skills

Skills / Requirements

• Prior experience in the Supply Chain industry as an analytics / Data Science / BI professional
• Knowledge of Upstream / Downstream Supply chain and business drivers
• The incumbent is responsible for working on a range of technologies and tools collaborating directly with the central MSC stakeholders, MSC asset focal teams across different business
• Experience in SAP systems specifically in Plant maintenance (PM) and Materials management modules (MM)
• Applied Data science expertise in Demand & Supply Chain planning/forecasting, Inventory planning/optimization, Material management, Spend Analytics.
• Proficiency Level: Skill-to-Mastery

Technical Skills

• Deep expertise in quantitative fields (Statistics / Mathematics) and comfortable in working with a large amount of data
• Expertise in Inferential statistics, Multivariate Analysis, Time Series, Machine learning techniques (supervised and unsupervised), and Text Mining
• Strong experience in Data Science tools and technologies like Python, R, PowerBI, Alteryx, Spotfire
• Ability to search, extract, load & visualize data from databases using pre-defined reports and new ad hoc queries (using BI self-service)
• Strong analytical mindset and a real passion for Data, drilling data for insight, and learning new things every day in a pro-active way
• Capacity to present the data by storytelling in an easy and compelling way

Stakeholder Engagement Skills

• Working collaboratively across multiple sets of stakeholders – business SMEs, IT, Data experts/engineers, R&D teams, UI/UX designers to deliver on project deliverables and tasks
• User-focused – Continuous engagement with end-users and align any solution development to their needs
• Ability to articulate complex data science models to business teams and present the insights in easily understandable and innovative formats
• Ability to proactively recommend multiple approaches along with their pros & cons to the stakeholders and support making the right decisions
• Proficiency Level: Skill-to-Mastery

Data Scientist at TCS

Location: Chennai, Tamil Nadu

Required Technical Skill Set:

• Machine learning and Deep learning skills: Python, Pyspark, OpenCV, Tensorflow or PyTorch, Scikit learn
• Cloud Platform skills: Microsoft Azure Machine Learning or Amazon Web Services Sage Maker
• Visualization Tools: Plotly, Seaborn, Streamlit

Must-Have :

1. Python with Machine learning or Deep learning packages

2. Pyspark

3. Tensorflow

4. Microsoft Azure Machine Learning or Amazon Web Services Sage Maker

5. Plotly or Seaborn or Streamlit

6. A graduate or postgraduate in Engineering in Mechanical, Chemical, Electrical or Electronics with strong mathematical background

Good-to-Have :

1. Solid background in the fundamentals of formulation of the problem statements, system modeling, and machine learning for solving industrial problems.

2.  Skilled in data visualization techniques and handling data engineering ETL of large sets of time series

3. Ability to apply multiple algorithms or architectures of ML or DL and recommend the best model with explainability

4. Build, train and test data science models with First principle-based engineering model of machine or process using data from IoT system

5. Very good Communication and Presentation skills

Responsibility of / Expectations from the Role:

• The associate will be working on building Cognitive business solutions that will give actionable insights by the systematic application of machine learning techniques and deep learning techniques
• Ability to interpret complex Industrial business requirements and translating them into analytical problems to deliver high-value outputs
• A dedicated individual with a commitment towards continuous learning and apply engineering knowledge, Mathematics, Statistics to build an AI model of state of art research

The post TOP DATA SCIENCE JOBS ONE CAN APPLY FOR THIS WEEKEND appeared first on Artificial Intelligence.

Machine learning is gaining popularity across scientific and technical fields, but it’s often not clear to researchers, especially young scientists, how they can apply these methods in their work.

Machine learning (ML), loosely defined as the “ability of computers to learn from data without being explicitly programmed,” has become tremendously popular in technical disciplines over the past decade or so, with applications including complex game playing and image recognition carried out with superhuman capabilities. The Earth and space sciences (ESS) community has also increasingly adopted ML approaches to help tackle pressing questions and unwieldy data sets. From 2009 to 2019, for example, the number of studies involving ML published in AGU journals approximately doubled.

In many ways, ESS present ideal use cases for ML applications because the problems being addressed—like climate change, weather forecasting, and natural hazards assessment—are globally important; the data are often freely available, voluminous, and of high quality; and computational resources required to develop ML models are steadily becoming more affordable. Free computational languages and ML code libraries are also now available (e.g., scikit-learn, PyTorch, and TensorFlow), contributing to making entry barriers lower than ever. Nevertheless, our experience has been that many young scientists and students interested in applying ML techniques to ESS data do not have a clear sense of how to do so.

The Tools of the Trade

An ML algorithm can be thought of broadly as a mathematical function containing many free parameters (thousands or even millions) that takes inputs (features) and maps those features into one or more outputs (targets). The process of “training” an ML algorithm involves optimizing the free parameters to map the features to the targets accurately.

There are two broad categories of ML algorithms relevant in most ESS applications: supervised and unsupervised learning (a third category, reinforcement learning, is used infrequently in ESS). Supervised learning, which involves presenting an ML algorithm with many examples of input-output pairs (called the “training set”), can be further divided, according to the type of target that is being learned, as either categorical (classification; e.g., does a given image show a star cluster or not?) or continuous (regression; e.g., what is the temperature at a given location on Earth?). In unsupervised learning, algorithms are not given a particular target to predict; rather, an algorithm’s task is to learn the natural structure in a data set without being told what that structure is.

Supervised learning is more commonly used in ESS, although it has the disadvantage that it requires labeled data sets (in which each training input sample must be tagged, or labeled, with a corresponding output target), which are not always available. Unsupervised learning, on the other hand, may find multiple structures in a data set, which can reveal unanticipated patterns and relationships, but it may not always be clear which structures or patterns are “correct” (i.e., which represent genuine physical phenomena).

Applications in Earth and Space Sciences

Books and classes about ML often present a range of algorithms that fall into one of the above categories but leave people to imagine specific applications of these algorithms on their own. However, in practice, it is usually not obvious how such approaches (some seemingly simple) may be applied in a rich variety of ways, which can create an imposing obstacle for scientists new to ML. Below we briefly describe various themes and ways in which ML is currently applied to ESS data sets (Figure 1), with the hope that this list—necessarily incomplete and biased by our personal experience—inspires readers to apply ML in their research and catalyzes new and creative use cases.

1. Pattern Identification and Clustering

One of the simplest and most powerful applications of ML algorithms is pattern identification, which works particularly well with very large data sets that cannot be traversed manually and in which signals of interest are faint or highly dimensional. Researchers, for example, applied ML in this way to detect signatures of Earth-sized exoplanets in noisy data making up millions of light curves observed by the Kepler space telescope. Detected signals can be further split into groups through clustering, an unsupervised form of ML, to identify natural structure in a data set.

Conversely, atypical signals may be teased out of data by first identifying and excluding typical signals, a process called anomaly or outlier detection. This technique is useful, for example, in searching for signatures of new physics in particle collider experiments.

2. Time Series and Spatiotemporal Prediction

An important and widespread application of supervised ML is the prediction of time series data from instruments or from an index (or average value) that is intended to encapsulate the behavior of a large-scale system. Approaches to this application often involve using past data in the time series itself to predict future values; they also commonly involve additional inputs that act as drivers of the quantities measured in the time series. A typical example of ML applied to time series in ESS is its use in local weather prediction, with which trends in observed air temperature and pressure data, along with other quantities, can be predicted.

In many instances, however, predicting a single time series of data is insufficient, and knowledge of the temporal evolution of a physical system over regional (or global) spatial scales is required. This spatiotemporal approach is used, for example, in attempts to predict weather across the entire globe as a function of time and 3D space in high-capacity models such as deep neural networks.

3. Emulators and Surrogates

Traditional, physics-based simulations (e.g., global climate models) are often used to model complex systems, but such models can take days or weeks to run on even the most powerful computers, limiting their utility in practice. An alternate solution is to train ML models to act as emulators for physics-based models or to replicate computationally intensive portions within such models. For example, global climate models that run on a coarse grid (e.g., 50- to 100-kilometer resolution) can include subgrid processes, like convection, modeled using ML-based parameterizations. Results with these approaches are often indistinguishable from those produced by the original model alone but can run millions or billions of times faster.

4. Boundary or Driving Conditions

Many physics-based simulations proceed by integrating a set of partial differential equations (PDEs) that rely on time-varying boundary conditions and other conditions that drive interior parts of the simulation. The physics-based model then propagates information from these boundary and driver conditions into the simulation space—imagine, for example, a 3D cube being heated at its boundary faces with time-varying heating rates or with thermal conductivity that varies spatiotemporally within the cube. ML models can be trained to reflect the time-varying parameterizations both within and along the simulation boundaries of a physical model, which again may be computationally cheaper and faster.

5. Interpretability and Knowledge Discovery

If a spatiotemporal ML model of a physical system can be trained to produce accurate results under a variety of input conditions, then the implication is that the model implicitly accounts for all the physical processes that drive that system, and thus, it can be probed to gain insights into how the system works. Certain algorithms (e.g., random forests) can automatically provide a ranking of “feature importance,” giving the user a sense of which input parameters affect the output most and hence an intuition about how the system works.

More sophisticated techniques, such as layerwise relevance propagation, can provide deeper insights into how different features interact to produce a given output at a particular location and time. For example, a neural network trained to predict the evolution of the El Niño–Southern Oscillation (ENSO), which is predominantly associated with changes in sea surface temperature in the equatorial Pacific Ocean, revealed that precursor conditions for ENSO events occur in the South Pacific and Indian Oceans.

6. Accelerating Inversions

A ubiquitous challenge in ESS is to invert observations of a physical entity or process into fundamental information about the entity or the causes of the process (e.g., interpreting seismic data to determine rock properties). Historically, inverse problems are solved in a Bayesian framework requiring multiple runs of a forward model, which can be computationally expensive and often inaccurate. ML offers alternative methods to approach inverse problems, either by using emulators to speed up forward models or by using physics-informed machine learning to discover hidden physical quantities directly. ML models trained on prerun physics-based model outputs can be used for rapid inversion.

7. Creating High-Resolution Global Data Sets

Satellite observations often provide global, albeit low-resolution and sometimes indirect (i.e., proxy-based), measurements of quantities of interest, whereas local measurements provide more accurate and direct observations of those quantities at smaller scales. A popular and powerful use for ML models is to estimate the relationship between global proxy satellite observations and local accurate observations, which enables the creation of estimated global observations on the basis of localized measurements. This approach often includes the use of ML to create superresolution images and other data products.

8. Uncertainty Quantification

Typically, uncertainty in model outputs is quantified using a single metric such as the root-mean-square of the residual (the difference between model predictions and observations). ML models can be trained to explicitly predict the confidence interval, or inherent uncertainty, of this residual value, which not only serves to indicate conditions under which model predictions are trustworthy (or dubious) but can also be used to generate insights about model performance. For instance, if there is a large error at a certain location in a model output under specific conditions, it could suggest that a particular physical process is not being properly represented in the simulation.

9. Physics-Informed Neural Networks

Domain experts analyzing data from a given system, even in relatively small quantities, are often able to extrapolate the behavior of the system—at least conceptually—because of their understanding of and trained intuition about the system based on physical principles. In a similar way, laws and relationships that govern physical processes and conserved quantities can be explicitly encoded into neural network algorithms, resulting in more accurate and physically meaningful models that require less training data.

10. Finding and Solving Governing Equations

In certain applications, the values of terms or coefficients in PDEs that drive a system—and thus that should be represented in a model—are not known. Various ML algorithms were developed recently that automatically determine PDEs that are consistent with the available physical observations, affording a new and powerful discovery tool.

In still newer work, ML methods are being developed to directly solve PDEs. These methods offer accuracy comparable to traditional numerical integrators but can be dramatically faster, potentially allowing large-scale simulations of complex sets of PDEs that have otherwise been unattainable.

Addressing Urgent Challenges

The Earth and space sciences are poised for a revolution centered around the application of existing and rapidly emerging ML techniques to large and complex ESS data sets being collected. These techniques have great potential to help scientists address some of the most urgent challenges and questions about the natural world facing us today. We hope the above list sparks creative and valuable new applications of ML, particularly among students and young scientists, and that it becomes a community resource to which the ESS community can add more ideas.

Acknowledgments

We thank the AGU Nonlinear Geophysics section for promoting interdisciplinary, data-driven research, for supporting the idea of writing this article, and for suggesting Eos as the ideal venue for dissemination. The authors gratefully acknowledge the following sources of support: J.B. from subgrant 1559841 to the University of California, Los Angeles, from the University of Colorado Boulder under NASA Prime Grant agreement 80NSSC20K1580, the Defense Advanced Research Projects Agency under U.S. Department of the Interior award D19AC00009, and NASA/SWO2R grant 80NSSC19K0239 and E.C. from NASA grants 80NSSC20K1580 and 80NSSC20K1275. Some of the ideas discussed in this paper originated during the 2019 Machine Learning in Heliophysics conference.

The post Ten Ways to Apply Machine Learning in Earth and Space Sciences appeared first on Artificial Intelligence.

AI and data science jobs are already seen as a rewarding career path for professionals

Artificial intelligence is a promising technology, that has made significant changes in the 21st century. Starting from self-driving cars and robotic assistants to automated disease diagnosis and drug discovery, the stronghold of artificial intelligence is no joke. Along with artificial intelligence, data science has also shifted the way we live and work. With the demand for data science and artificial intelligence spiralling, the job market is opening its door to AI and data science jobs. The tech sphere has ensured that artificial intelligence jobs and data science jobs provide limitless opportunities for professionals to explore cutting edge solutions. According to a Gartner report, Artificial intelligence jobs rose to over 2.3 million in 2020. While the competition in the industry is heating up, AI and Data science jobs are already seen as the rewarding career path. Analytics Insight has listed top AI and Data science jobs that aspirants should apply for today.

• LATEST PLACEMENT ALERT: TOP HIGHEST PAYING TECH JOBS TO APPLY IN 2021
• DATA SCIENCE JOBS ALERT: TOP OPENINGS TO APPLY FOR THIS WEEK
• PLACEMENT ALERT: TOP DATA ANALYTICS JOBS OF THE YEAR 2021 IN INDIA

Data Scientist: Artificial Intelligence at IBM–

Location: Bengaluru, Karnataka, India

About the company: IBM, also known as International Business Machines Corporation is a leading American computer manufacturer. The company has developed a thoughtful, comprehensive approach to corporate citizenship that they believe aligns with IBM’s values and maximized the impact they can make as a global enterprise.

Roles and responsibilities: As a data scientist at IBM, the candidate is expected to develop, maintain, and evaluate AI solutions. He/she will be involved in the design of data solutions using artificial intelligence-based technologies like H2O, Tensorflow. They are responsible for designing algorithms and implementation including loading from disparate datasets, pre-processing using Hive and Pig. The candidate should scope and deliver solutions with the ability to design solutions independently based on high-level architecture. They should also maintain the production systems like Kafta, Hadoop, Cassandra, and Elasticsearch.

Qualifications

• The candidate should have a minimum of 4 years of experience in the IT industry.
• They should be technologically wise in Python programming and have proficient skills in Watson NLP.
• He/she should know to develop and embed AI solutions in Intelligent Workflow.
• The candidate should have working knowledge in one NoSQL database like MongoDB, Cassandra, HBase, or Couchbase.
• They should have hands-on experience in big data architectures.

Senior Analyst- Artificial Intelligence Innovation at Accenture–

Location: Bengaluru, Karnataka, India

About the company: Accenture is a global professional services company that provides a range of services and solutions in strategy, consulting, digital, technology, and operations. Combining deep experience and specialized skills across 40 industries and business functions, Accenture works at the intersection of business and technology to help clients improve performance and create sustainable value for stakeholders.

Roles and responsibilities: As a senior analyst- artificial intelligence innovation, the candidate will be aligned with Accenture’s insights and intelligence vertical and help them generate insights by leveraging the latest artificial intelligence and analytics techniques to deliver value to its clients. Generally, the artificial intelligence innovation team at Accenture is responsible for the creation, deployment, and managing of the operations of projects. In this role, the candidate will need to analyze and solve increasingly complex problems. He/she should frequently interact with their peers at Accenture and clients to manage the development well.

Qualifications

• The candidate is mandated to own a B.E/B.Tech/M.Tech degree.
• He/she should have at least 5-8 years of experience in working with artificial intelligence.

Principal, Artificial Intelligence Engineer at AT&T–

Location: Azcapotzalco, Mexico City, Mexico

About the company: AT&T is a US-based telecom company and the second largest provider of mobile services. AT&T operates as a carrier of both fixed and mobile networks in the US but offers telecoms services elsewhere. The company also provides pay-TV services through DirecTV.

Roles and responsibilities: The artificial intelligence engineer at AT&T is responsible for designing and implementing artificial intelligence and machine learning packages, including data pipelines, to process complex, large-scale datasets used for modelling, data mining, and research purposes. He/she is expected to design, develop, troubleshoot, debug, and modify software for AT&T services or the management and monitoring of these service offerings. They should interact with systems engineers t realize the technical design and requirements of the service, including management, systems, and data aspects.

Qualifications

• The candidate is expected to have a Bachelors degree in Computer Science, or Scientific Computing, Data Analytics, Machine Learning, Business Analyst nanodegree, or any equivalent experience.
• He/she should have experience working with Java, Python, SQL, Azure, etc.

Data Engineer at LinkedIn–

Location: Bengaluru, Karnataka, India

About the company: LinkedIn is a social networking site designed to help people make business connections, share their experience and resumes, and find jobs. LinkedIn is free, but a subscription version called LinkedIn Premium offers additional features like online classes and seminars.

Roles and responsibilities: As a data engineer at LinkedIn, the candidate is expected to work with a team of high-performing analytics, data science professionals, and cross-functional teams to identify business opportunities, optimize product performance or go to market strategy. He/she should build data expertise and manage complex data systems for a product or a group of products. They should perform all the necessary data transformation tasks to serve products that empower data-driven decision-making. The candidate should establish efficient design and programming patterns for engineers as well as for non-technical partners.

Qualifications

• The candidate is mandated to have Bachelors in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
• He/she should have 3+ years of experience working with a large number of datasets.
• They should have hands-on experience in SQL and relational databases.
• The candidate should have experience with distributed data systems such as Hadoop and related technologies like Spark, Presto, Pig, Hive, etc.

Data Scientist, Engineering at Google–

Location: Bengaluru, Karnataka, India

About the company: Google is an American search engine company founded in 1998. Began as an online search firm, the company now offers more than 50 internet services and products including email, online document creation, software for mobile phones and tablet computers, etc.

Roles and responsibilities: As a data scientist at Google, the candidate will evaluate and improve Google’s products. They will collaborate with a multi-disciplinary team of Engineers and Analysts on a wide range of problems, bringing analytical rigour and statistical methods to the challenges of measuring quality, improving consumer products, and understanding the behaviour of end-users, advertisers, and publishers. He/she should work with large, complex data sets and solve difficult, non-routine analysis problems by applying advanced methods. The candidate should conduct end-to-end analysis, including data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.

Qualifications

• The candidate should have a Master’s degree in a quantitative discipline or equivalent practical experience.
• He/she should have at least 2 years of experience in data analysis or a related field.
• They should be well-versed in statistical software.

Data Engineer at Tata Consultancy Services-

Location: Melbourne, Victoria, Australia

About the company: Tata Consultancy Services, also known as TCS, is a global leader in IT services, digital, and business solutions. The company partners with clients to simplify, strengthen, and transform their business.

Roles and responsibilities: As a data engineer, the candidate should design and build production data pipelines from ingestion to consumption within a big data architecture, using Java, Python, or Scala. He/she should design and implement data engineering, ingestion, and curation functions on AWS cloud using AWS native or custom programming.

Qualifications

• The candidate is expected to have 4+ years of experience working with AWS cloud, Big data technologies, AWS Cloud Data Services like RedShift, Lambda, Glue, etc.
• He/she should have the experience to build, design, and operationalize enterprise data solutions and applications using one or more AWS data and analytics services.
• They should have experience in ETL Tools, data modelling, data analysis, Python, Shell scripting, ETL Testing, Splunk tools, etc.

The post GRAB THE OPPORTUNITY: TOP AI AND DATA SCIENCE JOBS TO APPLY TODAY appeared first on Artificial Intelligence.

AI and data science jobs are already seen as a rewarding career path for professionals

Artificial intelligence is a promising technology, that has made significant changes in the 21st century. Starting from self-driving cars and robotic assistants to automated disease diagnosis and drug discovery, the stronghold of artificial intelligence is no joke. Along with artificial intelligence, data science has also shifted the way we live and work. With the demand for data science and artificial intelligence spiralling, the job market is opening its door to AI and data science jobs. The tech sphere has ensured that artificial intelligence jobs and data science jobs provide limitless opportunities for professionals to explore cutting edge solutions. According to a Gartner report, Artificial intelligence jobs rose to over 2.3 million in 2020. While the competition in the industry is heating up, AI and Data science jobs are already seen as the rewarding career path. Analytics Insight has listed top AI and Data science jobs that aspirants should apply for today.

• LATEST PLACEMENT ALERT: TOP HIGHEST PAYING TECH JOBS TO APPLY IN 2021
• DATA SCIENCE JOBS ALERT: TOP OPENINGS TO APPLY FOR THIS WEEK
• PLACEMENT ALERT: TOP DATA ANALYTICS JOBS OF THE YEAR 2021 IN INDIA

Data Scientist: Artificial Intelligence at IBM–

Location: Bengaluru, Karnataka, India

About the company: IBM, also known as International Business Machines Corporation is a leading American computer manufacturer. The company has developed a thoughtful, comprehensive approach to corporate citizenship that they believe aligns with IBM’s values and maximized the impact they can make as a global enterprise.

Roles and responsibilities: As a data scientist at IBM, the candidate is expected to develop, maintain, and evaluate AI solutions. He/she will be involved in the design of data solutions using artificial intelligence-based technologies like H2O, Tensorflow. They are responsible for designing algorithms and implementation including loading from disparate datasets, pre-processing using Hive and Pig. The candidate should scope and deliver solutions with the ability to design solutions independently based on high-level architecture. They should also maintain the production systems like Kafta, Hadoop, Cassandra, and Elasticsearch.

Qualifications

• The candidate should have a minimum of 4 years of experience in the IT industry.
• They should be technologically wise in Python programming and have proficient skills in Watson NLP.
• He/she should know to develop and embed AI solutions in Intelligent Workflow.
• The candidate should have working knowledge in one NoSQL database like MongoDB, Cassandra, HBase, or Couchbase.
• They should have hands-on experience in big data architectures.

Senior Analyst- Artificial Intelligence Innovation at Accenture–

Location: Bengaluru, Karnataka, India

About the company: Accenture is a global professional services company that provides a range of services and solutions in strategy, consulting, digital, technology, and operations. Combining deep experience and specialized skills across 40 industries and business functions, Accenture works at the intersection of business and technology to help clients improve performance and create sustainable value for stakeholders.

Roles and responsibilities: As a senior analyst- artificial intelligence innovation, the candidate will be aligned with Accenture’s insights and intelligence vertical and help them generate insights by leveraging the latest artificial intelligence and analytics techniques to deliver value to its clients. Generally, the artificial intelligence innovation team at Accenture is responsible for the creation, deployment, and managing of the operations of projects. In this role, the candidate will need to analyze and solve increasingly complex problems. He/she should frequently interact with their peers at Accenture and clients to manage the development well.

Qualifications

• The candidate is mandated to own a B.E/B.Tech/M.Tech degree.
• He/she should have at least 5-8 years of experience in working with artificial intelligence.

Principal, Artificial Intelligence Engineer at AT&T–

Location: Azcapotzalco, Mexico City, Mexico

About the company: AT&T is a US-based telecom company and the second largest provider of mobile services. AT&T operates as a carrier of both fixed and mobile networks in the US but offers telecoms services elsewhere. The company also provides pay-TV services through DirecTV.

Roles and responsibilities: The artificial intelligence engineer at AT&T is responsible for designing and implementing artificial intelligence and machine learning packages, including data pipelines, to process complex, large-scale datasets used for modelling, data mining, and research purposes. He/she is expected to design, develop, troubleshoot, debug, and modify software for AT&T services or the management and monitoring of these service offerings. They should interact with systems engineers t realize the technical design and requirements of the service, including management, systems, and data aspects.

Qualifications

• The candidate is expected to have a Bachelors degree in Computer Science, or Scientific Computing, Data Analytics, Machine Learning, Business Analyst nanodegree, or any equivalent experience.
• He/she should have experience working with Java, Python, SQL, Azure, etc.

Data Engineer at LinkedIn–

Location: Bengaluru, Karnataka, India

About the company: LinkedIn is a social networking site designed to help people make business connections, share their experience and resumes, and find jobs. LinkedIn is free, but a subscription version called LinkedIn Premium offers additional features like online classes and seminars.

Roles and responsibilities: As a data engineer at LinkedIn, the candidate is expected to work with a team of high-performing analytics, data science professionals, and cross-functional teams to identify business opportunities, optimize product performance or go to market strategy. He/she should build data expertise and manage complex data systems for a product or a group of products. They should perform all the necessary data transformation tasks to serve products that empower data-driven decision-making. The candidate should establish efficient design and programming patterns for engineers as well as for non-technical partners.

Qualifications

• The candidate is mandated to have Bachelors in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
• He/she should have 3+ years of experience working with a large number of datasets.
• They should have hands-on experience in SQL and relational databases.
• The candidate should have experience with distributed data systems such as Hadoop and related technologies like Spark, Presto, Pig, Hive, etc.

Data Scientist, Engineering at Google–

Location: Bengaluru, Karnataka, India

About the company: Google is an American search engine company founded in 1998. Began as an online search firm, the company now offers more than 50 internet services and products including email, online document creation, software for mobile phones and tablet computers, etc.

Roles and responsibilities: As a data scientist at Google, the candidate will evaluate and improve Google’s products. They will collaborate with a multi-disciplinary team of Engineers and Analysts on a wide range of problems, bringing analytical rigour and statistical methods to the challenges of measuring quality, improving consumer products, and understanding the behaviour of end-users, advertisers, and publishers. He/she should work with large, complex data sets and solve difficult, non-routine analysis problems by applying advanced methods. The candidate should conduct end-to-end analysis, including data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.

Qualifications

• The candidate should have a Master’s degree in a quantitative discipline or equivalent practical experience.
• He/she should have at least 2 years of experience in data analysis or a related field.
• They should be well-versed in statistical software.

Data Engineer at Tata Consultancy Services-

Location: Melbourne, Victoria, Australia

About the company: Tata Consultancy Services, also known as TCS, is a global leader in IT services, digital, and business solutions. The company partners with clients to simplify, strengthen, and transform their business.

Roles and responsibilities: As a data engineer, the candidate should design and build production data pipelines from ingestion to consumption within a big data architecture, using Java, Python, or Scala. He/she should design and implement data engineering, ingestion, and curation functions on AWS cloud using AWS native or custom programming.

Qualifications

• The candidate is expected to have 4+ years of experience working with AWS cloud, Big data technologies, AWS Cloud Data Services like RedShift, Lambda, Glue, etc.
• He/she should have the experience to build, design, and operationalize enterprise data solutions and applications using one or more AWS data and analytics services.
• They should have experience in ETL Tools, data modelling, data analysis, Python, Shell scripting, ETL Testing, Splunk tools, etc.

The post GRAB THE OPPORTUNITY: TOP AI AND DATA SCIENCE JOBS TO APPLY TODAY appeared first on Artificial Intelligence.

The jobs related to data science are in high demand worldwide because of their high salary and interesting ground of work. Data scientists are analytical experts who utilize their skills in both technology and social science to find trends and manage data. They apply industry knowledge, contextual understanding, skepticism of existing assumptions – to uncover solutions to business challenges. A data scientist’s work typically involves making sense of messy, unstructured data, from sources such as smart devices, social media feeds, and emails that don’t neatly fit into a database. The following are the top data scientist jobs, which one can apply for this week.

Data Scientist at Wipro

Location: Chennai, Tamil Nadu

About the company

Wipro India Business, a part of Wipro Limited is a leading global IT transformation, consulting, and business process services provider and a pioneer in the Indian market with decades of experience. They harness the power of application, cognitive computing, hyper-automation, robotics, cloud, analytics, and emerging technologies to help their clients adapt to the digital world and make them successful.

Roles and Responsibilities

Suitable candidates will be part of Wipro Digital-Intelligent Enterprise practice. The role entails leveraging Data Science and Machine Learning to solve typical problems within the organization and create IP that could be deployed in a productized mode. This will entail significant hands-on work on multiple Big Data Technologies, Data Analysis, identifying data patterns, ML models, and insights generation. The role entails deployment in a customer context and managing customer expectations.

Skills Required:

• Missing Data Imputation, Outlier Treatment
• Scaling, Normalization, Standardization
• Encoding for Categorical Variables
• Oversampling\Undersampling for reducing the class imbalance

Data Analyst at Amazon

Location: Bengaluru, Karnataka

About the company

Amazon teams in India work on complex business challenges to innovate and create efficient solutions that enable various Amazon businesses, including Amazon websites across the world as well as support Payments, Transportation, Cloud,  and Digital products and services like the Kindle family of tablets, e-readers and the store.

Roles and responsibilities

The company is looking for a hands-on, detail-oriented, and highly motivated data analyst to help create data-backed insights that will drive selection improvement. The candidate should be comfortable interfacing with technology systems and be able to analyze data and gather actionable conclusions. Operating in a rapidly changing environment will require the candidate to be adept at dealing with ambiguous, new, and challenging situations. The candidate must be comfortable in executing repeatable processes.

Skills Required

• Experience with E-Commerce, Retail, and Business Analytics would be an advantage.
• Understanding of data warehousing, data modeling concepts, and building new DW tables.
• Advanced SQL skills, fluent in R and/or Python, advanced Microsoft Office skills, particularly Excel and analytical platforms.

Data Analyst at PayPal

Location: Chennai, Tamil Nadu

About the company

Fueled by a fundamental belief that having access to financial services creates opportunity, PayPal (NASDAQ: PYPL) is committed to democratizing financial services and empowering people and businesses to join and thrive in the global economy. Their open digital payments platform gives PayPal’s 392 million active account holders the confidence to connect and transact in new and powerful ways, whether they are online, on a mobile device, in an app, or in person. Through a combination of technological innovation and strategic partnerships, PayPal creates better ways to manage and move money and offers choice and flexibility when sending payments, paying, or getting paid. Roles and responsibilities

An ideal candidate for this job will have to be innovative & curious. One should have the desire and ability to connect and empathize with the customers. One should possess an entrepreneurial spirit and get excited about creating new businesses and re-inventing current ones. One should be analytical & action-oriented, data-driven and outcome-focused. One should grow comfortable with ambiguity, fueled by a hunger to learn and constantly seeking out new challenges. One should be collaborative & team-oriented, always keeping the people around in the loop and are excited to communicate complex ideas clearly to make sure the co-workers understand the “why” behind their work and their key priorities.

Skills Required:

• Experience with or willingness to learn tools such as SQL, R, Python.

Data Science Intern at Sony Research India

Location: Bengaluru, Karnataka

About the company

Sony Research India Private Limited was established in July 2020 as a research company in India as part of Sony’s global R&D centers. Delivering Excitement, Passion, Joy, and Compassion to the World, all is possible with the diverse research opportunities they offer at Sony Research India. We venture into entertainment, healthcare, music, and gaming. They also devise mobility solutions that help people get around securely and safely and support creators to expand their creativity with innovative AI applications. Sony Research India is a place to apply a wide range of technologies to inspire emotion in new fields.

Roles and responsibilities

Together with the head of data science & team of data scientists, work on the research & development activities daily and contribute to reporting, coding, testing, and implementing relevant models. Also, some other responsibilities, but not limited to, will be scraping data from the public domain and researching the content recommendation for the OTT platforms.

Skills Required:

• Python coding
• Statistics
• Strong SQL theoretical knowledge
• ML basics

Data Scientist at LinkedIn

Location: Bengaluru, Karnataka

About the company

LinkedIn connects the world’s professionals to make them more productive and successful. With more than 756 million members worldwide, including executives from every Fortune 500 company, LinkedIn is the world’s largest professional network. The company has a diversified business model with revenue coming from Talent Solutions, Marketing Solutions, Sales Solutions, and Premium Subscription products. Headquartered in Silicon Valley, LinkedIn has offices across the globe.

Roles and responsibilities

• Work with a team of high-performing analytics, data science professionals, and product managers to identify business opportunities and optimize member experiences at LinkedIn.
• Reporting and Monitoring: Design, create and automate reports and dashboards to track key business metrics in security Engineering and security product areas. ETL data, clean and validate data when needed.
• Product Analytics: Design and analyze experiments to test new product/feature ideas and convert the results into actionable business recommendations. Formulate success metrics for initiatives, create and automate dashboards/reports to monitor them and quickly identify the root cause of the anomaly.
• End-to-end Deep Dive Analytics: Deep dive into an area, find insights and understand the root cause of an observed trend, and translate the insights into actionable recommendations. When applicable, implement the solution and monitor the performance. Analyze and mine both structured and unstructured data to drive member-centric insights.

Skills Required:

• Relevant experiences in security analytics, risk analytics, trust & safety analytics from high-tech companies.
• Experience in applied statistics and statistical modeling in at least one statistical software package, (eg. R, SPSS)
• Advanced degree in quantitative fields – Computer Science, Engineering, Operational Research, Mathematics, Statistics, Economics, etc.
• Strong business mindset and strong problem-solving skills
• Excellent communications skills. The candidate should be able to explain complex problems to a variety of audiences. The candidate should be able to drive meetings and lead discussions

The post DATA SCIENCE JOBS ALERT: TOP OPENINGS TO APPLY FOR THIS WEEK appeared first on Artificial Intelligence.

Land a career in AI with these top artificial intelligence jobs.

Artificial intelligence job prospects have grown in recent years as industry demand has expanded. The rumor that AI will generate a slew of new jobs is correct. Artificial intelligence appears to provide more opportunities than any other profession now available.

We’ve compiled a list of Pepsico Artificial Intelligence Job Openings that you can apply for right now.

• HOW MUCH DOES ARTIFICIAL INTELLIGENCE COST IN 2021?
• THE SEXIEST ARTIFICIAL INTELLIGENCE DESIGNATIONS IN INDIA OF 2021
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Architect, AI/ML Developer

Location: Hyderabad, Telangana

Responsibilities:

• This role will lead technical development within Artificial Intelligence/Machine Learning for PBNA Advanced Analytics. This will include design, implement, and maintain digital solutions for the PBNA sector.
• Set up and manage the company’s AI development and facilitate production infrastructure.
• Help AI product managers and business stakeholders understand the potential and limitations of AI when planning new products.

Architect – Robotic Process Automation (RPA) Lead Engineer

Location: Hyderabad, Telangana

Responsibilities:

• As an Automation Lead Engineer, you will be responsible for leading a team to the developer.
• You will work closely with teams to develop, test, implement new and existing automation processes.
• You will be exposed to a wide array of business applications that get tied together with the company’s robots and will create value for the organization by automating business tasks.

Architect – Data Science

Location: India

Responsibilities:

• This role will lead technical development within Artificial Intelligence/Machine Learning for PBNA Advanced Analytics. This will include design, implement, and maintain digital solutions for the PBNA sector. The role is responsible for:
• Set up and manage the company’s AI development and facilitate production infrastructure.
• Help AI product managers and business stakeholders understand the potential and limitations of AI when planning new products.
• Build data ingest and data transformation infrastructure.

Architect, Scrum Master, Azure, Data Science

Location: Hyderabad, Telangana

Responsibilities:

• As part of AMESA/APAC Data and Digital Solutions team, the job requires driving the automation, e-commerce, and Data Science, Data Modelling, Data Ingestion agenda.
• The person will deliver and lead development for EDW, Data Lake, Business Intelligence, Azure, and Advanced Analytics.
• One will be playing the role of scrum master across multiple projects.

Associate Director, SAP Cloud Infrastructure

Location: Hyderabad, Telangana

Responsibilities:

The Associate Director, Cloud Acceleration & Value Office will be responsible for the design, build, and deployment of infrastructure and environments required on private/public cloud for PepsiCo global SAP program – PepsiCo Global Template (PGT). This role is part of PepsiCo’s Acceleration & Cloud Office – a multi-discipline team responsible for architecting and delivering secure, robust, and innovative solutions which would enable the development teams to build and deploy new applications as well as migrate selected existing applications into the public cloud. The candidate will work alongside SAP solution architecture, Basis and Environment, Cloud Operations teams to design, build, deploy and sustain the systems and landscape.

Sr. ML Engineer

Location: Plano, TX

Responsibilities:

• Partner with a data scientist working on discovery, prototypes, and pilot. Focus on experiment tracking
• Partner with data engineers regarding data pipelines and data versioning.
• Coordinate work activities with IT services and as required.
• Drive the use of the Platform toolset.
• Build, deploy or publish machine learning models that run efficiently in cloud pipelines.
• Help drive optimization, testing, and tooling to improve quality (unit tests).

R&D Ana Tech Director (Director, Data Science – AI & ML)

Location: Valhalla, NY

Responsibilities:

• Provide leadership and strategy for AI/ML platforms to support R&D innovations and internal partners.
• Contribute to R&D digital strategy and be a liaison between AI/ML COE, the R&D stakeholders, IT, and vendors.
• Translate business needs and requirements into technical concepts and solutions.
• Work with Business as the AI/ML COE leader to understand the digital technology requirements, define the business problems and deliver solutions.
• Lead, develop, and inspire a high-performing team to build and scale solutions for R&D innovations.

ML Engineer

Location: Cornellà de Llobregat, Catalonia, Spain

Responsibilities:

• Partner with a data scientist working on discovery, prototypes, and pilot. Focus on experiment tracking.
• Work with data engineers regarding data pipelines and data versioning.
• Adopt the best MLOps standards to design and develop scalable end-to-end machine learning pipelines.
• Build and deploy machine learning models that run in cloud pipelines.

The post LATEST ARTIFICIAL INTELLIGENCE JOBS AT PEPSICO YOU CAN APPLY FOR RIGHT NOW appeared first on Artificial Intelligence.

Land a career in AI with these top artificial intelligence jobs in 2021.

There is no doubt that advanced technologies have become essential in today’s businesses worldwide. Technology, particularly artificial intelligence, is providing organizations opportunities to drive business growth and innovation. Along with the ubiquitous adoption of technology, jobs in artificial intelligence are surging at an exponential rate. Analytics insight estimates that there will be 10,06,945 job openings in artificial intelligence in 2021. In India, the demand will continue rapidly with the government’s steps towards digitization and the emergence of startups and companies. The average artificial intelligence salary in India is INR 534,000, according to Glassdoor.

Here’s the list of top artificial intelligence jobs you can apply for in February 2021.

CGI Group, Inc.

Job Role: AI and ML Developer

Location: Bangalore

Job Description:

CGI is at the center of digital transformation, supporting its clients’ digital journeys and offering professionals exciting career opportunities. The company is looking for AI and ML developers. Candidates for this position must have the ability to design, develop and implement AI and ML algorithms. They should have hands-on experience in at least 2-3 Deep Learning & AI Framework and machine learning coding languages.

Requirements:

• Should have knowledge of Python and artificial intelligence.

• Experience of 2-3 ML/Data science Tools, two development tools, and 2-3 data exploration and visualization tools.

• Must have worked on 3 to 4 projects implementing AI and ML algorithms and productionalizing the same.

• Must have good communication skills and is a good team player.

• Ability to lead a project from start to finish and guide other members who are new to AI-ML, and more.

NVIDIA

Location: Pune

Job Role: Senior Software Engineer – Deep Learning

Job Description:

NVIDIA is currently seeking an experienced software engineer with strong Deep Learning and System Programming fundamentals coupled with robust C/C++ skills. The selected candidate will contribute to the development of the NVIDIA RTX Broadcast engine, a comprehensive suite of SDKs and libraries that enable AI-driven features for game broadcasting, video conferencing and content creation. He/she will architect and lead the development of next-generation deep learning and multimedia algorithms for the processing of audio and video applications.

Requirements:

• D./MS in Computer Science or a closely related engineering field with 10+ years of relevant experience.

• Strong background in Deep Learning including model design, pruning & performance optimization, transfer learning, etc.

• 4+ years of experience of leading cross-module projects and taking them to productization.

• Strong software engineering background with proficiency in C or C++.

• Hands-on expertise with PyTorch, TensorRT, CuDNN and one or more Deep Learning frameworks (Tensorflow, Keras, etc), and more.

StarTele Logic

Location: Noida

Job Role: Artificial Intelligence Developer – Machine Learning/Deep Learning

Job Description:

The ideal candidate will be responsible for using NLP and ML techniques to bring order to unstructured data. He/she should have experience in the latest techniques in AI, NLP, machine learning, including Deep Learning approaches. The aspirant will work within the engineering team to design, code, train, test, deploy and iterate on enterprise-scale machine learning systems.

Requirements:

• Experience in applying machine learning techniques, Natural Language Processing or Computer Vision.

• Strong analytical and problem-solving skills.

• Solid software engineering skills across multiple languages including but not limited to Java or Python, CC++.

• Problem solver: able to work independently, and be comfortable with deadlines and milestones.

• Deep understanding of ML techniques such as classification, clustering, deep learning, optimization methods, supervised and unsupervised techniques, and more.

Novartis

Location: Telangana

Job Role: Procurement Data Scientist – NLP

Job Description:

The selected candidate will be required to design, develop and deliver various data science-based insights, outcomes and innovation. He/she will create “proof of concepts & blueprints” to drive faster, timely, highly precise, workable and proactive decision-making based on data-driven insights and science and shape the strategic glidepath of the company. The candidate should think creatively, conceptualize and lead projects resulting in substantial long-term impact on the company’s vision in many key strategic areas such as drug discovery/manufacturing, product launches, expanding patient access, risk mitigation, brand management, etc.

Requirements:

• S/Ph.d in Computer Science, Robotics, Mathematics, Statistics, Engineering, Finance, Economics, Medicine, Technology, and other related disciplines.

• 6 -10 years of overall experience with a demonstrated track record in data science solutions.

• Exposed to concepts in NLP & Statistics, esp., in their application such as Sentiment Analysis, Contextual NLP, Dependency, Parsing, Chunking, Summarization, etc.

• Comfortable in using Python or R to build automated dashboards, and more.

EY

Location: Bangalore

Job Role: TTT – Manager – AI

Job Description:

As a member of EY’s core Tax practice, the ideal candidate will develop a deep tax technical knowledge and outstanding database, data analytics and programming skills. He/she will be required to apply machine learning techniques to deliver actionable insights. The candidate will be responsible for model development – manipulation including data exploration, training data, feature extraction and model development, validation and scoring on structured and unstructured data and to highlight patterns, anomalies, relationships and trends, and more.

Requirements:

• Bachelors / Master’s degree in Science or Statistics / Engineering / MCA/ MBA.

• An overall experience of 4+ years of which 2-3 years of hands-on work experience with AI and ML techniques and tools such as neural networks, regression, classification and clustering, NLP, ARIMA algorithms.

• A couple of years of experience with data sources and platforms such as Unix/Linux, Teradata, Hadoop, and SQL Server.

• Expertise in software such as R, Python, Java or C++, and more.

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