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.

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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.

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

Companies everywhere are pouring resources into artificial intelligence (A.I.) and machine learning (ML) initiatives. Many technologists believe that apps “smartened” with A.I. and ML tools will eventually offer better customer personalization; managers hope that A.I. will lead to better data analysis, which in turn will power better business strategies.

But which industries are actually hiring A.I. specialists? If you answer that question, it might give you a better idea of where those resources are being deployed. Fortunately, CompTIA’s latest Tech Jobs Report offers a breakdown of A.I. hiring, using data from Burning Glass, which collects and analyzes millions of job postings from across the country. Check it out:

Perhaps it’s no surprise that manufacturing tops this list; after all, manufacturers have been steadily automating their production processes for years, and it stands to reason that they would turn to A.I. and ML to streamline things even more. In theory, A.I. will also help manufacturers do everything from reducing downtime to improving supply chains—although it may take some time to get the models right. 

The presence of healthcare, banking, and public administration likewise seem logical. “These three industries have the money to invest in A.I. and ML right now and have the greatest opportunity to see the investment pay off, fast,” Gus Walker, director of product at Veritone, an A.I. tech company based in Costa Mesa, California, told Dice late last year.“That being said, the pandemic has caused industries hit the hardest to take a step back and look at how they can leverage AI and ML to rebuild or adjust in the new normal.”

Compared to overall tech hiring, the number of A.I.-related job postings is still relatively small. Right now, mastering and deploying A.I. and machine learning is something of a specialist industry; but as these technologies become more commodified, and companies develop tools that allow more employees to integrate A.I. and ML into their projects, the number of job postings for A.I. and ML positions could increase over the next several years. Indeed, one IDC report from 2020 found three-quarters of commercial enterprise applications could lean on A.I. in some way by 2021.

It’s also worth examining where all that A.I. hiring is taking place; it’s interesting that Washington DC tops this particular list, with New York City a close second; Silicon Valley and Seattle, the nation’s other big tech hubs, are somewhat further behind, at least for the moment. Washington DC is notable not only for federal government hiring, but the growing presence of companies such as Amazon that hunger for talent skilled in artificial intelligence:

Jobs that leverage artificial intelligence are potentially lucrative, with a current median salary (according to Burning Glass) of $105,000. It’s also a skill-set that more technologists may need to become familiar with, especially managers and executives. “A.I. is not going to replace managers but managers that use A.I. will replace those that do not,” Rob Thomas, senior vice president of IBM’s cloud and data platform, recently told CNBC. If you mention A.I. or ML on your resume and applications, make sure you know your stuff before the job interview; chances are good you’ll be tested on it. 

The post Which Industries are Hiring A.I. and Machine Learning Roles? appeared first on Artificial Intelligence.

Big data and data analytics jobs around the world.

Big Data is a big thing in today’s world with tremendous growth opportunities for professionals. As companies around the world are aggressively hiring data professionals to extract insights for their businesses, data analysis has become a striking career choice. Organizations across industries want to take advantage of big data to stay ahead of the competition.

A big data scientist or a data analyst, if you’re a data professional looking for a big, new project, check out these full-time, big data job openings in renowned companies across the globe. To help you crack the interview stage, check out these popular big data interview questions and answers.

1. Senior Insights Analyst

Company: LinkedIn

Location: Sunnyvale, CA

Job Summary

As a Senior Insights Analyst in the Product Operations organization, you will leverage one of the richest proprietary data sets in the world to create compelling, impactful, and actionable insights for the company, and the product and operations teams. Your expertise will help LinkedIn deepen the intelligence from its member/customer signals, and elevate the quality of the company’s products.

Responsibilities

• Leverage Linkedin’s unique data to drive insights and learnings for product improvement.
• Build and scale insights to help our teams deliver exceptional products and services to all members and customers.
• Partner closely with our Product Operations teams to turn data into action, and provide recommendations to influence and shape the product strategy and roadmap.
• Write SQL/Presto/Spark/Python queries to extract, blend and analyze structured and unstructured data, and present the findings in Tableau and PowerPoint.
• Partner and execute with Data Science, Business Intelligence, Engineering to ensure foundational data are available and accurate for insights tools and analyses.
• Build analytical tools, products, and dashboards to democratize insights and enhance our collective storytelling ability.
• Apply statistical models and causal inference methods to uncover trends, measure impact, and predict the future performance of our product.
• Connect signals we have from our members and customers across, including but not limited to: customer support cases, social media mentions, behavioral data on the platform, and more.
• Help develop the predictive analytics engine in partnership with Data Science to project the impact of friction reduction in products.
• Own the analytical framework, and provide methodology & measurement for new product quality metrics like user success & sentiment.
• Collaborate closely with product, operations, engineering teams to provide analysis, reporting, and tool-building capabilities that inform our key stakeholders.
• Proactively identify opportunities to scale insights through automation and self-serve mechanisms.
• Coach and uplevel our signals and product quality teams on tools, analytics, and insight.

Qualifications

• 5+ years experience in analytics or quantitative role.
• Degree in math, statistics, economics, or related quantitative field.
• 3+ years experience in a role requiring research, data interrogation, analysis, and visualization.
• 5+ years of experience writing and optimizing SQL queries to extract trends.

Preferred Qualifications

• MA/MS/Ph.D. in math, statistics, economics, or related quantitative field.
• Experience in a role requiring influencing R&D and measuring product impact.
• Ability to convert a complex data set into an actionable recommendation.
• Ability to communicate findings clearly to both technical and non-technical audiences.
• Experience in the Technology, Product, and/or Consultative industry providing actionable insights.
• Experience with Hadoop and/or Python for ETL, and working with big data.
• Experience with statistical modeling, Python/R scripts, and packages.
• Experience with experimental design and A/B testing.
• Experience with Tableau, or other data visualization software.
• Experience with working cross-functionally with data services, engineering, product, and operations teams.
• Knowledge of social media and consumer Internet practices.

2. Data Analyst, Globalization

Company: Netflix

Location: Los Gatos, CA

Job Summary

As a Data Analyst, you will collaborate with Netflix’s Analytics Program Manager and other Globalization team members, to support the data and infrastructure that translate business requirements into operational excellence. You will learn everything about Globalization data in order to provide relevant and valuable insights into its performance. You will use your analytical capabilities to create Globalization- and Netflix-ready dashboards to review, measure and manage the business.

Responsibilities

• Track and maintain data integrity across multiple tools and workflows; identify and resolve data inconsistencies.
• Prepare regular business health and insights decks for globalization.
• Build and manage external-facing reporting for the team.
• Build and maintain data ingestion pipelines.
• Perform ad hoc analyses and queries as necessary (for requests that cannot be answered via existing dashboards).
• Provide analytical support for initiatives (that are fairly straightforward but might require complex analytics).
• Collaborate with the Analytics Program Manager to create an optimized business operations framework against which the Globalization team can perform and support translation at scale.
• Develop and maintain effective communication tools to report business performance and drive business decisions both internally (vendor QBRs and newsletters) and externally (dashboards) for globalization.

Qualifications

• BA/BS degree in Data Analytics, Business, Finance, or Operations.
• 3+ years of experience in consulting, business operations, or data analytics at a global scale.
• Required Skills: advanced SQL, advanced python (pandas & NumPy, data visualization libraries), ETL, Tableau (or similar dashboard platforms); experience with Jupiter notebooks preferred.
• Excellent analytical skills with experience managing and utilizing large data sets to drive performance and process improvement.
• Strong communication skills with the ability to effectively communicate risks and dependencies, and to distill complex concepts into simple, actionable recommendations at the leadership level.
• Drive decisions and change management through data analysis, collaboration, and leadership.

3. Data Analyst

Company: Twitch

Location: San Francisco, CA

Job Summary

Twitch’s Viewers Analytics team is looking for a product data analyst. The Viewers team develops customer-facing products that connect viewers and streamers, such as Browse, Search, Notifications, and Recommendations. As part of the Viewers Analytics team, you will improve the quality and velocity of product decisions made in the Viewers team. You will instrument tracking events, gather data, suggest metrics, design AB tests, build dashboards, and produce insights for your product partners. You will report to the Viewers Analytics Lead.

Responsibilities

• Become a domain expert at the product surface your support, building trust with your product partners.
• Ensure your product, engineering, and design partners understand and use the insights you produce.
• Automate data monitoring requests and frequently asked questions in dashboards.
• Troubleshoot data quality issues, communicate their impact, and propose solutions or workarounds.
• Distill complex problems and highlight trade-offs between solutions, with the help of product partners and analyst mentors.

Qualifications

• Great SQL skills, so you can quickly tap into our data sources.
• A clear understanding of hypothesis testing, p-values, and bootstrap methods, so you can explain them to product partners unfamiliar with statistics.
• At least 6 months of experience transforming data into insights in a related industry, or equivalent data analytics experience. Internships count!
• Experience using Python data libraries like pandas, NumPy, or scipy.

Preferred Qualifications

• Experience designing and analyzing AB tests in a tech company.
• Product analytics experience with signup funnels, engagement metrics, and retention analysis.
• Python programming experience beyond data or analytics.
• Experience developing Tableau dashboards.
• Familiarity with Git or other version control tools.
• Passion about online communities and games, frequent Twitch user.

4. Senior Data Analyst and Modeler

Company: JPMorgan Chase & Co.

Location: Glasgow, Scotland

Responsibilities

• Analyze and catalog files and processes which are currently sources of data specific to the domain of interest of transactions & positions.
• research, design, document, and modify data specifications throughout the production life cycle. Data will be available in diverse formats ranging from Text files, databases, JSON, Kafka messages, etc.
• Analyze the requirements from the consumers based on your understanding of the Conformed model, model source data to the model enhancing the same where necessary.
• Take into account the limitations of the underlying tech infrastructure and cater the solution so that it can be implemented and is maintainable.
• Develop productive business relationships and integrate activities with IT team members, Quality Assurance, Software Development, and Database Administration teams, to ensure successful deployment and support of Production issues and various Projects/Assignments handled in the Applications domain.
• Work collaboratively with stakeholders to facilitate and positively influence solution development and ongoing support. Maintains confidentiality of the information and uses information appropriately.
• Exhibits sound judgment when making decisions and recommendations and serve as the conduit between the customer community (internal clients) and the software development team through which requirements flow.

Qualifications

• Bachelor’s Degree with specialized coursework in Computer Science or Management Information Systems.
• Significant years of experience as a data analyst and/or modeler.
• Knowledge of Wealth Management & associate accounting is a must.
• Extremely proficient with SQL and using SQL to analyze data.
• Knowledge of Big Data and Hadoop platforms, Kafka, Cassandra are a plus
• Ability to operate effectively in ambiguous situations.
• Ability to learn quickly, manage work independently, and is a team player.
• Ability to engage with developers & stakeholders including – consumers, project management, upstream, senior management & peer group.

5. Senior Analyst

Company: eBay

Location: London, United Kingdom

Job Summary

eBay is looking for a senior analyst to join the UK Analytics team with significant responsibility for delivering business Analytics. The London-based team specifically manages the UK Trading businesses and supports the EU Marketplace Businesses by creating and delivering actionable analytics insights to support UK business performance and develop a deeper understanding of business drivers and opportunities mainly focused on Seller Performance, Customer Insights, Promotions, and Pricing.

Responsibilities

• Support Business Decision-making through data-driven Actionable Insights.
• Apply your expertise in quantitative analysis and the presentation of data to see beyond the numbers and understand how our users interact with our core products.
• Work with Business Partners to scope analysis to answer key business questions – challenge their thinking and become a trusted business partner. Help the business prioritize analytical deliverables and manage their expectations.
• Measure and interpret the impact of business initiatives and new products and features.
• Develop and deliver the business story from the analysis and effectively communicate this to business and finance partners.
• Providing weekly updates on business performance to finance, cost, and promotional teams.
• Insight Analytics including ad-hoc deep dives, cost estimation, and forecasting, etc.
• Identify, extract and analyze relevant information from multiple data sources (primarily Teradata).
• Assess internal/external factors that may influence customer usage and important metrics.
• Be the Customer: Buy, Sell, and Engage with eBay’s mission of connected commerce.

Qualification

• An established analytical career as a Data Scientist/BI/Insight Analyst preferably within e-commerce, consumer web, retail, media, digital marketing, or consultancy environment.
• Graduate degree (ideally in a quantitative field).
• Proven ability in clearly defining a problem, collating the required information, analyzing the results, and presenting findings and recommendations.
• Ability to initiate and drive projects to completion with minimal mentorship.
• Strong technical and financial modeling skills with commercial business insight.
• Advanced level skills in SQL and Tableau and Excel are a requirement. R Desirable
• Proven experience in the analysis of relational databases e.g. Teradata or Hadoop and strong SQL/SAS/R programming skills.
• Experience in working with big data, including data extraction & optimization techniques, and reporting/visualization, in particular using data visualization tools.
• Experience in web analytics is not essential but useful.
• Fluency in English is a requirement.
• Excellent communication skills.

6. Data Analyst

Company: AXA UK

Location: Glasgow, Scotland

Responsibilities

• Extract data from primary and secondary sources. Format and interpret the data so it can easily be understood, analyze data using statistical techniques.
• Work with a variety of data tools and databases, designing solutions, maintaining data, creating, updating, reading, and deleting records.
• Collect data from multiple sources, handle raw data, cleanse data and convert it into structured formats ready for further analytics and data science.
• Work with big data in a data lake on a cloud platform.
• Work and collaborate with other data professionals; data engineers, MI engineers, data scientists.
• Work with business stakeholders to communicate with data, preparing reports, analyzing KPIs and other metrics.
• Create and maintain business glossary, data dictionaries and classify data according to local priorities.
• Implement data by design processes along with Data Architects, DPO, and other stakeholders.

Qualifications

• Mathematical skills (especially statistics and probability).
• Strong excel skills, experience in working with and manipulating data.
• Experience with visualization tools and reporting packages (e.g. Power BI).
• Experience with relational databases, SQL language, ETL frameworks. Knowledge of Python and R desirable.
• Adept at queries, report writing, and presenting findings.
• Knowledge of data management and data governance practices including data protection.
• Strong oral and written communication skills, autonomy, curiosity, rigorous in execution, team player and able to coordinate a network of stakeholders from various backgrounds, ability to understand business needs.
• Strong problem-solving capability.
• Knowledge of agile methodology/MS Devops desired.
• Desired experience and knowledge of Salesforce.

7. Research Analyst – Technology Advantage

Company: Boston Consulting Group (BCG)

Location: Madrid, Spain

Job Summary

As a Research Analyst within BCG’s Data & Researcher Services team, you would provide secondary research in support of proposals, client cases, and business or IP development initiatives, with specialization in one or more Technology Advantage related topics.

Technology Advantage topics covered by the team on a regular basis include Digital/IT, Big Data, Agile, IT/Tech Infrastructure, Enterprise Architecture, Cloud, AI, and Digital Transformation. You will be responsible for delivering a variety of requests throughout the day.

Responsibilities

• Manage various research requests with a high-level accuracy and organization, primarily on key Technology Advantage topics you have a strong interest in.
• Understand request objectives focussed on Technology and IT industry and proactively suggest the most appropriate and efficient research approach to senior DRS team members and customers, as appropriate.
• Evaluate the source quality and data accuracy, and proactively help to identify and raise research-related issues.
• Engage in thought partnership with consulting teams and knowledge teams to understand, scope, and deliver accurate, timely, and relevant data and information.
• Coaching Research Associates and outsourcing partners, as well as delivering data quality analysis with them.
• Along with collecting, summarizing and synthesizing relevant data and information into appropriate, concise, timely, and highly effective output, you are proficient in Excel, Word, and PowerPoint.
• With guidance, you will develop tools, resources, and training within the Technology Advantage topic, you will be contributing to knowledge capture and documentation.
• Using your strong analytical thinking, you will provide advanced synthesis, and develop deep expertise in specialized research tools, databases and sources.
• In addition to being intellectually curious and being able to work in a fast-paced, deadline-focused environment, you can identify practical, timely, and innovative research approaches.

Qualifications

• 2-4+ years relevant working experience, with some specialization in 1-2 topics in Digital/IT, Big Data, Agile, IT/Tech Infrastructure, Enterprise Architecture, AI, Cloud, and Digital Transformation sectors.
• Bachelor’s degree with a strong preference for analytic programs (e.g. economics, engineering, sciences).
• Excellent English; + fluent in another European language (German preferred, Spanish).
• Hours of operation for DRS will be 9:00 am – 18:00 CET. Your regular full-time work week will be 40 hours a week.

8. Junior Data Analyst

Company: NielsenIQ

Location: Warsaw, Poland

Job Summary

Data Analyst works in the operational part of a global business unit called Retail Direct Data Solution. This global team, present in countries such as France, UK, the US, Australia, Romania, and Poland, provides clients from and outside Europe with stock management solutions aimed at improving on-shelf availability. The key purpose of the job is to develop and maintain key business metrics for Global clients to assess the sales/stocks effectiveness. As a Data Analyst, you will be designing, testing, and validating the logic for new metrics, you will create different excel-based reports associated with the validation of the new logic and cooperate on a daily basis with the Business Analyst.

Responsibilities

• Work on designing, testing, and validating the logic for new metrics solutions to our clients.
• Deep data analysis for various data sets.
• Control the creation and release of analytics internally and to our clients (this involves scheduling work with offshore resources).
• Maintain documentation for solutions.
• Mentor junior members of the offshore and onshore teams.
• Create efficiencies in the way we manage our global analytics requirements by establishing global ways of working.
• Organize and support a library of solutions available to provide information to other departments and to make it easier to support.

Qualifications

• 1+ years of analytical experience, working with data/databases in a large company.
• Proficiency in Excel (Advanced level).
• Fluent command of English.
• Proven track record of being detail-oriented, client service driven, and committed to the timely execution of tasks.
• Experience with R/Python language usage in regular work will be a plus.
• Experience in cooperation with off-shore resources will be a plus.

9. Senior Analyst – FP&A

Company: Spotify

Location: Stockholm, Sweden

Job Summary

The FP&A team is responsible for owning and managing the company’s financial forecasting process as well as partnering with business stakeholders to enable and drive financially informed decision-making. As a Senior Analyst, you will have the exciting opportunity to grow and develop your skills as a finance business partner through various responsibilities, including financial modeling and analysis, forecasting and budgeting, management reporting, and data analytics.

Responsibilities

• Build and maintain detailed and dynamic financial models that are powered by big data to inform quarterly forecasts, budgeting/planning across the P&L, investment evaluation and prioritization, and commercial decision-making.
• Partner closely and regularly with both business and support teams to track business performance, exercise expenditure and investment controls, and identify risks and opportunities to our financial outlook.
• Manage and deliver on operational and analytical processes connected to each accounting period close, including accruals, variance analysis, management reporting, and/or model recalibrations as necessary.
• Use your communication and storytelling skills to frame issues effectively and translate the outputs of your financial analysis into impactful insights and compelling business recommendations.

Qualifications

• 5+ years of relevant, applied experience in finance/accounting, operations, strategy, consulting, or banking roles (exposure to SaaS, advertising, and/or content business models is preferred).
• Strong grasp of the 3 financial statements, with a high aptitude and enthusiasm for problem-solving through quantitative modeling and analysis.
• Advanced Excel / Google Sheets skills with a deep understanding of model architecture, formula efficiency, pivot tables, and macros.
• Savvy and experienced with forecasting, reporting, and procurement software (e.g., Adaptive, NetSuite, Coupa, etc.).
• Prior experience with SQL/BigQuery and BI/data visualization tools (Looker, Tableau) is a plus – you will be required to eventually learn and apply these skills on the job.
• Experience forming relationships across all levels of an organization and comfortable presenting to a broad range of audiences.
• Self-starter who is proactive, intellectually curious, and not afraid to seek out projects independently.
• Structured thinker with the ability to frame and reason through sophisticated business problems, even in the face of ambiguity or imperfect information.
• Strong communication and influencing skills, both verbal and written, as well as a collaborative mindset and approach to work.

10. Big Data Lead

Company: BARC India

Location: Mumbai, India

Job Summary

Manage Developments, Releases, and DevOps of high volume and complex data Processing Engine processing millions of rows every day using multiple processing algorithms and models. The chosen candidate should be able to handle multiple projects and be able to manage development cycles over multiple technology stacks.

Responsibilities

• Draft Understanding of big data requirements for providing solution design and managing development sprints.
• Documenting pipelines and strategizing automation.
• Document and manage end-to-end development, testing, and deployment tasks.
• Responsible for reviewing and optimizing existing ETL processes.
• Documentation and production support.
• Release management across multiple projects.
• Responsible for developing and managing workflows of various modules in the data validation pipeline.
• Delivery of big data reports over different data structures and transformation tools for resolving Ad-hoc business queries/reported bugs within SLAs.
• Delivering presentations to management on the team updates.
• Working knowledge for setting up cloud infrastructure and managing the same.

Qualifications

• Tech (Comp. Sc), BCA/MCA, or equivalent
• Minimum/Relevant Experience
• Total 10+ year experience
• 5+ years of experience in managing big data projects, and reports.
• 5+ years of experience in managing projects across technologies.
• 10 years of industry experience.
• Very strong and demonstrable hands-on experience managing Big Data Projects.
• Deep Knowledge of Hadoop, Spark, and Job Server Environment.
• Strong knowledge of Performance Tuning and Advanced Optimization.
• Knowledge of SQL / query languages and working with SQL as well as NoSQL databases.
• A good understanding of data structures and database management required.
• Analytical skills over Advanced SQL.
• Good knowledge of different technology stacks should be able to manage/mentor the development cycles.
• Expertise in High Volume Data Processing Production environment (not pilots or POCs).
• Knowledge of Git, SVN, and JIRA.
• Working knowledge on Jenkins.
• Good knowledge of AWS, EMR, and management of servers.
• Other programming languages like Java, C#, Kotlin, Objective C.
• Java Script frameworks like Angular/Vue/React.
• Good hold on Programming concepts like MVC, MVVC, Functional programming, OOP.
• Databases PostgreSQL and MongoDB

All the above information is taken from credible sources. To apply for the jobs above, visit the company’s official website and head over to the career section.

The post NOW HIRING! TOP BIG DATA JOB OPENINGS IN RENOWNED GLOBAL ORGANIZATIONS appeared first on Artificial Intelligence.

These artificial intelligence jobs can be your next big thing.

AI, the technology that is capable of raising eyebrows in the tech world, has a long way to go when it comes to developments. Organizations across industries are in the quest to utilize their power to gain a competitive edge and optimize their business processes. Hence, the demand for AI professionals across domains is evident. 

If you are an AI engineer or an AI scientist looking for the next big project, here are the top AI jobs from across the world.

1. AI/ML – Senior Analyst, Market Intelligence

Company: Apple 

Location: Seattle, USA 

Job Summary 

Apple is looking for a market intelligence analyst to conduct primary and secondary research on the AI market. The ideal candidate will be able to synthesize recent market news with long-term trends in the market to provide continual guidance to Siri engineering and product leadership on the direction of the market and any major shift identified. The ideal candidate would have experience performing market intelligence for voice assistants. 

Responsibilities 

•  Find and manage a group of primary, secondary, and tertiary data sources to provide accurate and up-to-date market information to engineering and product leadership.
• Synthesize data into customer-focused, meaningful insights that drive improvements to the customer experience.
• Provide regular long-term market forecasts on the AI space, including potential technologies and companies of interest.
• Provide continual updates to engineering and product leadership on significant changes in the market.
• Conduct research and analysis for internal partner teams to improve the feature-level experience.

Qualifications

• 10+ years of experience with market analysis and forecasting.
• Bachelors in Economics, Finance, Engineering or equivalent.
• Demonstrated accuracy in forecasting medium-term market trends in technology.
• Experience in contextualizing short term news in a broader context for senior executives.
• Competence in selecting primary, secondary, and tertiary data sources for review and reporting.
• Deep understanding of underlying technologies that are used by competitors in the market.
• Demonstrated experience in delineating primary drivers of risk and variance in market forecasts.

2. Research Scientist, AI 

Company: Facebook

Location: Seattle, USA 

Job Summary 

Facebook is seeking a Research Scientist to join Facebook AI Research (FAIR), a research organization focused on making significant progress in AI. Individuals in this role are expected to be recognized experts in identified research areas such as artificial intelligence, machine learning, computational statistics, and applied mathematics, particularly including areas such as deep learning, graphical models, reinforcement learning, computer perception, natural language processing, and data representation. The ideal candidate will have a keen interest in producing new science to understand intelligence and technology to make computers more intelligent.

Responsibilities 

• Lead research to advance the science and technology of intelligent machines.
• Lead research that enables learning the semantics of data (images, video, text, audio, speech and other modalities).
• Devise better data-driven models of human behavior.
• Work towards long-term ambitious research goals, while identifying intermediate milestones.
• Influence progress of relevant research communities by producing publications.
• Contribute research that can be applied to Facebook product development.
• Lead and collaborate on research projects within a globally based team.

Qualifications 

• Experience holding a faculty, industry, or government researcher position.
• Ph.D. and publications in machine learning, AI, computer science, statistics, applied mathematics, data science, or related technical fields.
• Experience leading a team in solving analytical problems using quantitative approaches.
• Experience manipulating and analyzing data from different sources.
• Experience in theoretical and empirical research and for answering questions with research.
• Experience communicating research for public audiences of peers.
• Knowledge in a programming language.
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Preferred Qualifications 

• 1+ year(s) of work experience in a university, industry, or government lab(s), in a role with primary emphasis on AI research.
• Experience driving original scholarship in collaboration with a team.
• First-author publications at peer-reviewed AI conferences (e.g. NIPS, CVPR, ICML, ICLR, ICCV, and ACL).
• Experience in developing and debugging in C/C++, Python, C# and/or Java.

3. AI Scientist 

Company: Electronic Arts (EA)

Location: Seattle, USA 

Job Summary 

The EADP Data Group develops a new unified Big Data pipeline across all franchises at Electronic Arts. This platform will incorporate data collection, ingestion, processing, access and visualization all built on a modern, cloud-based tech stack with outstanding tools. The Data Group will provide the tools and platform, which powers the future of game development, marketing, sales, accounting and customer experience. EA is looking for developers who want to work on a large-scale distributed data system from the ground up for one of the most creative, creative companies in technology.

Responsibilities 

• Develop state-of-the-art algorithms and extract important insights from EA’s rich store of data to empower intelligent agents within the EA ecosystem.
• Create scalable solutions for problems in the gaming domain.
• Design and evaluate highly creative AI applications for content creation, NPC behavior, game balance evaluation, and recommendations.
• Work with the core development teams to deploy AI applications as part of production systems.
• Establish scalable, efficient, automated processes for enterprise-level management of AI applications.
• Research and implement novel AI approaches for new problems.

Qualifications 

• Masters or PhD in Computer Science, or related fields (focus in AI or ML background).
• Experience having developed novel AI algorithms, and major journal and conference publication.
• Strong programming skills (object-oriented and functional paradigms).
• Experience with large-scale data and distributed systems – Experience with Apache Hadoop, Spark, and Tensorflow.
• 1+ years of experience with SQL and MPP databases.

4. Machine Learning Engineer, Content Platform 

Company: Spotify 

Location: London, England 

Responsibilities 

• Work in a high-performance, autonomous team of engineers and collaborate with researchers, designers and product managers across Spotify.
• Build audio processing pipelines in Python and data pipelines in Java.
• Take operational responsibility for the services that are owned by your team.
• Design and run experiments at scale, and communicate their results and importance to key stakeholders.
• Work in an environment that supports your individual growth by providing you challenging tasks to solve and the time needed to acquire new skills.

Qualifications 

• Bachelor’s degree (or equivalent) in computer science, machine learning, mathematics or related quantitative field, or extensive industry experience.
• Experience implementing and maintaining production machine learning systems at scale.
• Experience writing Python code and using Tensor Flow (or similar libraries such as PyTorch or Theano).
• Passionate about writing high-quality code.
• Excellent communication skills, both written and verbal.

5. Data and AI Consultant 

Company: Microsoft

Location: Belfast, Ireland 

Responsibilities 

• Be part of a thriving practice that is constantly looking for ways to improve the customers’ experience.
• Help translate business requirements into technology requirements for inclusion in contracts and/or statements of work.
• Craft both high-level and detailed design documents and implement innovative solutions using the most recent technologies.
• Optimize customer’s current data solutions and infrastructure.
• Implement a large data platform, business intelligence, advanced analytics and multi-tier type solutions.
• Take a leadership role on projects demonstrating experience handling projects through the entire project lifecycle. This includes running multi-phase/multi-dimensional/multi-resource projects to conclusion while maintaining high customer satisfaction.
• Continually learn and grow professionally.
• Mentor other consultants to share your knowledge and experience.

Qualifications 

• 2+ years of SQL Server or advanced database or advanced analytics experience.
• 3+ years of technical expertise in an enterprise environment.
• Deep technical or architectural knowledge of at least 2 of the following areas preferred:
• Database administration (preferably with SQL, including Azure SQL) – performance tuning, troubleshooting, high availability / disaster recovery, security.
• Database development (preferably with SQL, including Azure SQL) – designing and building database solutions (tables / stored procedures / forms / queries / etc.).
• Business intelligence – combining knowledge of SSIS/SSAS/SSRS/Power BI technologies with a deep understanding of data structure / data models to design, develop, and tune BI solutions and reports.
• Advanced data analytics – designing and building solutions using technologies such as Azure Data Factory, Azure Data Lake, HD Insights, SQL DWH, stream analytics, machine learning, R server.
• Big Data implementation – using Open Source and Non-SQL technologies such as Data bricks, Spark, Spark Streaming, Kafka, Storm, Zeppelin, Scala Software development, Hadoop Hive, Hadoop Map Reduce, Hadoop Clusters, Cosmos DB.
• B.S./B.A. or equivalent work experience combined with relevant industry experience in a consulting role.
• Ability to travel domestically and internationally and work with diverse cultures and customers and be able to obtain a valid passport within 90 days of joining the team.
• Fluency in written and spoken English and local language if applicable. Ability to speak other languages is a plus.
• Ability to communicate with a variety of different audiences and strong presentation skills.
• Ability to lead and motivate technical communities.
• Ability to effectively recognize and adapt to change.
• Ability to quickly grasp customers’ business challenges and drive positive change.

6. Lead AI Scientist 

Company: Builder.ai

Location: London, England 

Responsibilities 

• Exploit the knowledge in BKG at finding innovative applications of AI during end-to-end automated software management.
• Advance its state of the art in using representation learning to create embeddings that power various machine learning applications.
• Explore ideas around incorporating context to build personalized recommendation algorithms for targeted customer suggestions.
• Exploring the use of reinforcement learning or similar continuous learning principles to evolve the BKG.
• Take ideas from concept (possibly in academic literature) to production.

Qualifications 

• 6+ Years experience.
• 2+ years leading a team of at least 2-3 people.
• PhD in a scientific discipline with significant programming foundations such as Computer Science, Engineering, Physics among others.
• Proficient in programming in at least one high level programming language. Python experience preferable.
• At least 2 years of production experience in conceptualising, developing and productionising AI systems.
• Experience in building personalized recommender systems.
• Core understanding of representation learning.
• Core understanding of deep learning principles applied to structured and unstructured data.
• Experience in working within cross functional teams.
• Understanding product priorities and goals and aligning research, development and execution initiatives to such goals.
• Generating and testing hypotheses for future product features.
• Some background in knowledge graphs, optimization and reinforcement learning would be very beneficial.

7. Business Intelligence and Data Visualization

Company: Signal AI

Location: London, England 

Job Summary 

Signal AI is looking for a Business Intelligence & Data Visualization to work within its New Markets Delivery team. The team uses Signal’s data and technology to produce high-quality, fast turnaround reports and dynamic dashboards for its clients and public audiences. Signal AI is looking for someone excited by the idea of continuously working on new and varied projects. You will be working with a small, tightly-knit team producing reports and dashboards for a wide variety of audiences including clients, governments, journalists and Signal AI’s senior leadership. This role will give you the opportunity to explore many different facets of the business, including Delivery, Product and Data-Science, as well as gaining exposure to the Commercial side of the organization.

Responsibilities 

• Work independently and liaise directly with clients.
• Operate under high-pressure, returning work within very short time-frames.
• Demonstrate significant independent thinking, drawing insights from a wide variety of sources and data points, and then provide their own layer of analysis on top.
• Write fluently.
• Effectively use a wide number of research tools in order to find the right mix of opinion, fact and statistics for each brief or report.
• Consume a wide variety of sources from financial reports through to news or social media.
• Extract, process and interpret data sets and provide insightful commentary on items of interest.
• Directly brief senior figures both within and outside of Signal.

Qualifications 

• Excellent written communication skills.
• Strong research, analysis and summarization skills and an eye for interesting stories.
• Ability to produce work with tight deadlines.
• Experience working with 3rd parties.
• Experience scoping out requirements from its clients.
• You are proficient with the Office Suite (particularly Excel/Sheets).
• Experience working with APIs and building queries to extract data.
• Experience in working with BI tools such as Tableau and Power BI to create dynamic dashboards as well as generating ad hoc reports for New Markets.
• Experience querying APIs and confidence working with Python or similar.
• Experienced in dealing data quality issues and have a good understanding of end-to-end data flows.
• Comfortable creating functional and technical specifications and diagrams.

8. AI Engineer

Company: Elix Inc

Location: Tokyo, Japan 

Responsibilities 

• Research the latest technology and papers.
• Model development using deep learning and machine learning.
• Consult and implement project reports for clients.

Qualifications 

• Over 2 years of R&D experience using machine learning and deep learning.
• Over 4 years programming experience.
• Experience using and deep learning libraries such as PyTorch and TensorFlow.
• Ability to develop various deep learning models from scratch.
• Interests towards Deep Learning, Machine Learning and Computer Science.

Preferred Qualifications 

• Ph.D or equivalent experience in computer science, mathematics, physics, or equivalent practical skills

9. Data Scientist (Deep Learning)

Company: Binance 

Location: Singapore, Singapore 

Responsibilities 

• Conduct applied research and development in AI applications that involve computer vision, natural language processing, speech processing, and other related techniques.
• Work closely with other team members on implementing algorithms that power user focused products.
• Build and release models, and elevate customer experience and track impact over time.

Qualifications 

• MSc or PhD in Machine Learning, Computer Vision, Computer Science or Applied Mathematics with at least 5 years of relevant industry experience.
• Excellent hands-on experience with popular ML frameworks such as PyTorch or Tensor Flow.
• Fluent in English both written and spoken.
• Experience with application development practices at scale.

10. Senior Researcher – DSP and AI

Company: Dolby Laboratories 

Location: Sydney, Australia 

Job Summary

Dolby Laboratories is looking for a researcher who will be a cornerstone member of the team, developing novel algorithms and integrating them into demonstration platforms for new ideas and experiences. The team has the responsibility and high visibility to create solutions that help devices work together in an orchestrated way – to help users hear and be heard. Work will extend into real-time audio processing, system design, efficient communication protocols, and full-stack audio. The challenge and advances in audio processing will focus on managing input and output audio across distributed, uncertain, asynchronous audio devices. 

Responsibilities 

• Work with a research mindset that finds the right hypothesis and rejects/approves that through a set of experiments which thoroughly capture various aspects of that hypothesis.
• Having an “I’m willing to learn and make it work” attitude and work effectively with other team members to accomplish a task in a timely manner.
• Having the passion to constantly gain new skills and knowledge in a fast-paced environment with changing priorities.

Qualifications 

• Research track record (e.g. Industrial training, taste of research, undergraduate thesis, PhD dissertation, Postdoctoral proposal). Dolby Laboratories wants to see a track record of raising and testing hypotheses that really move a field of technology forward.
• A tertiary qualification (or equivalent) in Electrical Engineering, Computer Science or a related field with relevant industrial or academic experience as described below, specifically:
  • Bachelor’s Degree (or equivalent) and at least six years’ research work experience or
  • Master’s Degree (or equivalent) and at least four years’ research work experience or
  • PhD (or equivalent)
• Ability to implement an idea and prove a concept by writing a piece of robust code; proficiency in one or more of the following programming languages is required: Python, C, C++, MATLAB.
• Communicate hypotheses, background theory and experimental results clearly in meetings and written reports: Excellent English written and verbal communication in technology-specific applications is required.
• Work in a multi-functional team with constantly evolving tasks and changing priorities.

Preferred Qualifications 

• Deep understanding and work experience in one or more of
  • Audio DSP: Transforms, digital filtering, adaptive filtering
  • Real-world audio: Systems involving real world microphones and speakers
  • Audio AI: Deep learning algorithms and technologies and ML frameworks such as PyTorch.
  • Acoustic human perception: exploration of how we perceive sound and acoustics
• Ability to use the ear as a measurement tool.
• Higher degree education, masters or PhD

All the above information is taken from credible sources. To know more about the benefits and to apply for the job, head to the company’s official website and look for the careers section.

The post HIRING ALERT! HERE ARE THE HOTTEST AI JOBS ACROSS THE GLOBE appeared first on Artificial Intelligence.

The list represents top companies hiring data science professionals in Switzerland in March 2020

The world is powered by exponential data. With structured and unstructured data growing dramatically in companies’ data centers, organizations are looking for professionals who can work on sorting the data and make insightful decisions from it. This has led to a spike in the demand for data science professionals. The data science field is drastically evolving and the need to fill data science jobs is also growing. It is no different in Switzerland. Data science in Switzerland is also ballooning and the leading tech players are looking to hire data science professionals. Data scientists manage, mine, and clean unstructured data and prepare it for practical use. It is later used to deliver results that impact business outcomes. Some of the common data science jobs in Switzerland include data scientist, data analyst, data engineer, enterprise data architect, research scientist, etc. Analytics Insight has listed top companies hiring data science professionals in Switzerland in March 2020.

Data Scientist at Tata Consultancy Services

Tata Consultancy Services Ltd is an IT services, business solutions, and outsourcing organization that delivers real results to global businesses, ensuring a firm level of certainty. Founded in 1968 and initially based in India, the company now has a global presence, deep domain expertise in multiple industry verticals, and a rich portfolio of services such as consulting and service integration, digital transformation services, and cognitive business operations.

Job role and responsibilities: As a data scientist, the candidate should support the analysis of the data in Risk and Compliance area. He/she should prepare additional big data and data analysis technologies within the department, like data modelling, wrangling, pipelines implementation, etc. The candidate should build machine learning models on Palantir Foundry stack. He/she should review and methodologies to match clients via name matching.

Research Scientist at Microsoft

Location: Zurich, Switzerland

Microsoft Corporation is an American multinational technology company headquartered in Redmond, Washington. Microsoft is the leading developer of personal computer software systems and applications. The company also publishes books and multimedia titles, produces its own line of hybrid tablet computers, offers email services, and sells electronic game systems and computer peripherals. Founded in 1974, Microsoft is now well established across the globe.

Job role and responsibilities: The research scientist will work with an interdisciplinary team from conducting state of the art research to developing early prototypes to productization of technologies for social presence and action understanding in mixed reality. He/she should engage with the research community through publications, workshops or the supervision of interns & PhD students. The company demands the candidate to be self-motivated, strong as a team-player, should be a good communicator, and must accept challenges.

Data scientist at eBay

Location: Zurich, Switzerland

eBay Inc. is a global commerce leader that connects millions of buyers and sellers around the world. Founded in 1995, the company enables the economic opportunity for individuals, entrepreneurs, businesses, and organizations of all size. eBay portfolio of brands includes eBay Marketplace and eBay Classifieds Group, operating in 190 markets across the globe.

Job role and responsibilities: As the role is data-intensive, the data scientist is expected to be comfortable working with large sets of data and deliver business insights from the data using analytical techniques. He/she should be able to offer a strategic perspective, sound business judgement, and willing to work collaboratively with multiple teams in different geographies. The potential candidate should have a hands-on approach to data analysis, machine learning, strong intellectual curiosity, and a passion for achieving practical business impact.

Research scientist at DFINITY

Location: Zurich, Switzerland

The DFINITY Foundation is a not-for-profit organization based in Zurich, Switzerland, that oversees research centers in Palo Alto, San Francisco, Tokyo, and Zurich. The foundation’s mission is to build, promote, and maintain the internet computer and improve the world by doing so. The internet computer extends the functionality of internet from connecting billions of people to also providing million of developers and entrepreneurs with a public compute platform, creating a revolutionary new way to build websites, enterprise systems and internet services within an open environment.

Job role and responsibilities: As a research scientist, the potential candidate should collaborate with engineers to develop secure, reliable and scalable solutions, from problem identification and solution conception of production. He/she should provide deep technical insight in a field of interest and communicate it clearly. The candidate should contribute to designs and specifications of the next iterations of the Internet Computer.

Data engineer at SystemsAccountants

Location: Zurich, Switzerland

SystemsAccountants is a highly specialist recruitment and resourcing solutions company, focused exclusively on financial, accounting technology and transformation. The company specializes solely in sourcing, vetting and placing professionals who have a hybrid combination of financial/accounting experience and qualifications, blended with technology, project and change management expertise.

Job role and responsibilities: As a data engineer, the potential candidate will join fellow data enthusiasts, specializing in data engineering and integration. The team is responsible for integrating a wide range of Information Systems and helping make the best data available to the Data Insight team. The role involves significant projects while also managing support of existing ETL and Data pipelines.

The post TOP COMPANIES HIRING DATA SCIENCE PROFESSIONALS IN SWITZERLAND appeared first on Artificial Intelligence.

In terms of educational background, PayPal looks for candidates with programming, statistics, economics, and mathematics background with a focus on logical reasoning, data interpretation and a programming mindset.

PayPal, one of the largest online payment processing firm globally, has several data science teams working as Center of Excellence (CoE). For instance, Customer Support Intelligence focuses on research and development to solve NLP issues at scale. On the other hand, Global Data Science, Risk Analytics, Workforce Planning and Forecasting, Merchant & Consumer Analytics are focused on enabling Business/Risk/Compliance and work in a global construct.

We got in touch with V. Chandramouliswaran, Sr. Director, Global Financial Crimes and Customer Protection & Chennai Centre Head, PayPal India, to understand the hiring process for data scientists at the company. 

Skills Required

PayPal mainly focuses on two critical areas while hiring data scientists — functional skills and business. On the functional side, preference is given to candidates with machine learning skills, OpenCV and deep learning. “We also recruit many Business Analytics individuals for whom the data science functional experience requirement is less onerous,” said Chandramouliswaran.

On the business side, experience in payments, banking, risk, customer management, marketing experience is a huge plus.

In terms of educational background, PayPal looks for candidates with programming, statistics, economics, and mathematics background with a focus on logical reasoning, data interpretation and a programming mindset. “However, we have never focused on hiring only from top-tier institutes and are happy to provide opportunities to top talent with the right skill set and passion for solving large scale problems and driving global impact.”

“For us at PayPal, skills and educational background are not as important as experience and exposure,” added Chandramouliswaran. Candidates who have worked with big data, built data science models, solved pressing business problems are preferred.” We look to hire talent that constantly challenges us and pushes us to innovate every day.”

Interview Process

The interview process at PayPal consists of two significant steps:

Screening by talent acquisition and business teams: The first step is screening by the talent acquisition team, who spend about 20-45 minutes explaining the role and understanding the fitment. The business team then spends about 30-45 minutes explaining the roadmap, challenges and cultural fitment. 

Interview process: Post the screening, the candidate goes through an average of five rounds of interviews, each lasting 45-60 minutes covering the fundamentals of data science, ability to program and work with data, ML Libraries (for engineering DS roles) and also address a business case on analytics or model development.

Chandramouliswaran said one of the critical challenges in recruiting is the limited availability of talent for niche skill sets such as NLP and deep learning. Other challenges include a lack of understanding of the digital payments/fintech ecosystem’s nuances and strong business acumen. “Data scientists, in general, go around with a hammer in their hand looking for a nail, and that is the biggest challenge,” he said. 

Chandramouliswaran highlighted the typical mistakes in data scientists’ hiring process:

• Not doing due diligence and completing all key fundamentals of the hiring process. Late hire is always better than a wrong hire.
• Not following a consensus-driven approach.
• Not exposing the candidates to real-time business problems and consumer impacting decisions.

PayPal addresses such pitfalls by evaluating candidates based on their approach to solve real-time problems and implementing the solutions using a small dataset, and exposing the candidate to PayPal’s values, people, work and work culture. 

PayPal primarily relies on traditional ways to recruit data scientists, such as outbound efforts via job boards, campaigns, and referrals. Some of the non-traditional ways include connecting with potential talent during events, meet-ups and networking platforms.

PayPal posts most of the data science roles on its website. 

Interview Questions At PayPal 

The questions depend on the nature of the role. If the role has a heavy data science tilt, then the candidate would be expected to demonstrate a sound understanding of cutting-edge algorithms and will have to engage in a dialogue on ‘what’ works and ‘why’, explains Chandramouliswaran. 

For the Business Analytics role, guesstimate-type questions are asked. “Outside of these, there will be questions on the data skills that a person possesses, an ability to pull, scrub and analyse etc. Needless to say, the candidate needs to be comfortable with a programming language of his or her choice,” he said.

Being A Data Scientist At PayPal 

PayPal believes in inclusive hiring. The skill sets PayPal look for include: 

• Real-world data science problems solving skills
• Question the ‘why’ behind the problem and rejecting a one size fits all approach
• Strive to understand the business
• Always put the team ahead of themselves
• Identify themselves with PayPal’s values

A data scientist at PayPal is expected to carry responsibilities such as problem structuring, data preparation, model & strategy building, model & strategy validation, benefits measurement, and more. “A huge expectation is also in being comfortable with ambiguity. There have been many instances in which problems will be poorly defined, and having the requisite business background to engage in a dialogue to get to a well-defined and impactful problem statement collectively will be a differentiator,” he said.

Paypal provides ample opportunities for data scientists to grow through:

• Using real-time data to solve end-user problems
• Building landscapes that make technology more accessible for users who are not digital natives
• Working with large datasets that support critical decision-making
• Building consumer-friendly products and solutions

“With several data science functions located in India, careers can grow both laterally and vertically,” he said.

Pro Tips

For an analytics professional who wishes to carve out a career in the analytics industry, Chandramouliswaran advises them to be comfortable with data and numbers, and have an innate curiosity and problem-solving skills. “Building the right skill set through courses and competitions along with solving real-world problems will set the stage for people interested in analytics well on their way,” he said. 

The post Data Science Hiring Process At PayPal appeared first on Artificial Intelligence.

Data scientists at Bigbasket have to juggle multiple responsibilities since they are part of a small team supporting a growing and dynamic startup business.

The analytics and data science at Bigbasket is centrally located. Set up in 2013, the 10-member team works with various partners to focus on key business deliverables: analytics work products (reports, dashboards, deep-dives, etc. used by business teams directly) and data science work products (ML models, and OR models that power product features that benefit customers). The team also manages the end-to-end analytics ecosystem, including analytics infrastructure, analytics data pipelines, and deployment of analytical solutions and data science models. 

To understand more about the data science team and the hiring process, we got in touch with Subramanian MS, head of category marketing and analytics at Bigbasket. 

Required Skills

Subramanian said deep expertise and problem-solving skills are a must in an analytics professional. The expertise includes a solid understanding of algorithms, operation research and machine learning skills. “Some of the overarching traits we look for in all recruits include attention to detail, ownership and proactiveness etc. We believe these are key traits to succeed in the fast-paced, startup environment of Bigbasket,” he added. 

In terms of educational background, Bigbasket looks for engineering graduates with or without experience. As Subramanian shares, many of their team members have pursued and completed advanced machine learning and artificial intelligence programs before joining Bigbasket or, in some cases, while at Bigbasket.

Subramanian said some of the vital skills are problem-solving, analytical thinking, communication skills, attention to detail, ownership and proactiveness. Educational background is further used as a filter to shortlist candidates.

Interview Process 

Subramanian detailed the interview process for candidates, both experienced and fresher. 

The interview process for experienced candidates:

• SQL test since it is a critical skill used every day by analytics and data science professionals
• Setting up interviews with other team members to understand the cultural and experiential fit

The interview process for fresh hires:

• An assessment focused on understanding a candidate’s analytical, reasoning and verbal skills 
• Setting up interviews to help the candidate understand more about the opportunity and the interviewers to assess if the candidate will be a good fit

The traditional methods Bigbasket relies on recruiting are campus hiring, sourcing candidates through hiring partners and referral from Bigbasket employees. The non-traditional methods include a partnership with entities that offer online programs in analytics and data science, and social media, including LinkedIn.

The post Data Science Hiring Process At Bigbasket appeared first on Artificial Intelligence.

Like any new technology, artificial intelligence is capable of immensely good or bad outcomes. The public seems increasingly focused on the bad, especially when it comes to the potential for bias in AI. This concern is both well-founded and well-documented. But what is AI? It is the simulation of human processes by machines. This fear of biased AI ignores a critical fact: The deepest-rooted source of bias in AI is the human behavior it is simulating. It is the biased data set used to train the algorithm. If you don’t like what the AI is doing, you definitely won’t like what humans are doing because AI is purely learning from humans.

Let’s focus on hiring. The status quo of hiring is deeply flawed and quite frankly dystopian for three primary reasons.

Unconscious human bias makes hiring unfair. The typical way of reviewing applicants prior to an interview is through recruiters reviewing résumés. Numerous studies have shown this process leads to significant unconscious bias against women, minorities and older workers.

Large pools of applicants are being ignored. LinkedIn and other sourcing platforms have been so successful that, on average, 250 applicants apply for any open role. This translates into millions of applicants for a few thousand open roles. This process obviously cannot be handled manually. So, recruiters limit their review of the applicant pool to the 10% to 20% they think will show most promise: those coming from Ivy League campuses, passive candidates from competitors of the companies seeking to fill positions, or employee-referral programs. But guess what? Top colleges and employee-referral programs are much less diverse than the broader pool of applicants submitting résumés.

Traditional hiring tools are already biased. This is permitted by a loophole in U.S. law: Federal regulations state that a hiring tool can be biased if it is job-related. “Job-related” means that the people who are successful in a role show certain characteristics. But if all “successful employees” are white men, due to a history of biased human hiring practices, then it is almost certain that your job-related hiring assessment will bias towards white men and against women and minorities. An African American woman from a non-Ivy League college who is lucky enough to become part of the pipeline, whose résumé is reviewed, and who passes the human recruiter evaluating her résumé may then be asked to take a biased assessment.

Is it any wonder we struggle to hire a diverse workforce? What has led to today’s chronic lack of diversity, and what will continue to stunt diversity, are the human paradigms in place today, not AI.

AI holds the greatest promise for eliminating bias in hiring for two primary reasons:

1. AI can eliminate unconscious human bias. Many current AI tools for recruiting have flaws, but they can be addressed. A beauty of AI is that we can design it to meet certain beneficial specifications. A movement among AI practitioners like OpenAI and the Future of Life Institute is already putting forth a set of design principles for making AI ethical and fair (i.e., beneficial to everyone). One key principle is that AI should be designed so it can be audited and the bias found in it can be removed. An AI audit should function just like the safety testing of a new car before someone drives it. If standards are not met, the defective technology must be fixed before it is allowed into production.

2. AI can assess the entire pipeline of candidates rather than forcing time-constrained humans to implement biased processes to shrink the pipeline from the start. Only by using a truly automated top-of-funnel process can we eliminate the bias due to shrinking the initial pipeline so the capacity of the manual recruiter can handle it. It is shocking that companies today unabashedly admit how only a small portion of the millions of applicants who apply are ever reviewed. Technologists and lawmakers should work together to create tools and policies that make it both possible and mandatory for the entire pipeline to be reviewed.

Additionally, this focus on AI fairness should have us evaluate existing pre-hire assessments with the same standards. The U.S. Equal Employment Opportunity Commission (EEOC) wrote the existing fair-hiring regulations in the 1970s — before the advent of the public internet and the explosion in the number of people applying for each job. The EEOC didn’t anticipate modern algorithms that are less biased than humans yet also able to evaluate a much larger, more diverse pipeline. We need to update and clarify these regulations to truly encourage equal opportunity in hiring and allow for the use of algorithmic recruiting systems that meet clear criteria. Some precedents for standards have already occurred. The California State Assembly passed a resolution to use unbiased technology to promote diversity in hiring, and the San Francisco DA is using “blind sentencing” AI in criminal justice proceedings.

The same standards should be applied to existing hiring tools. Amazon was nationally lambasted for months due to its male-biased hiring algorithm. Yet in the United States today, employers are legally allowed to use traditional, biased assessments that discriminate against women or minorities. How can this be? Probably because most people are unaware that biased assessments are prominently used (and legal). If we are going to call for unbiased AI — which we absolutely should — we should also call for the elimination of all biased traditional assessments.

It is impossible to correct human bias, but it is demonstrably possible to identify and correct bias in AI. If we take critical steps to address the concerns that are being raised, we can truly harness technology to diversify the workplace.

The post Using AI to Eliminate Bias from Hiring appeared first on Artificial Intelligence.

Why are Indian startups looking for talent abroad? Well, the answer to this is the dearth of homegrown professionals on the ground with knowledge of UI/UX (user interface/user experience), artificial intelligence, machine learning, reports The Economic Times.

Industry experts are of the opinion that roles in data science and data engineering are not typically part of the curriculum of Indian colleges.

The ratio of the number of people to jobs in deep learning is 0.53, while for machine learning it’s 0.63 and for NLP it’s 0.71. Only 4 per cent of AI (Artificial Intelligence) professionals in India have worked on cutting-edge technologies such as deep learning and neural networks, the key ingredients in building advanced AI-related solutions, said Rishabh Kaul, co-founder of recruitment startup Belong.

Another reason for Indian startups to hunt for talent from overseas is to increase their global presence. Hence, these companies are either hiring foreign professionals or those Indians who wish to come back to India.

For the past two years, there have been a lot of global uncertainties, especially in the US. A lot of people are thinking of working from India and not the US. “The funds are normally coming from global companies and the startups are here, so it is best of both worlds as there’s a reverse brain drain,” said Rajeev Banduni, chief executive of advisory services firm GrowthEnabler, who has a lot of requests from European students, particularly the UK and Spain, for internships. He said 80-85 per cent talent is coming back to India.

UpGrad, started by UTV co-founder Ronnie Screwvala, is among those looking to expand presence in global markets. It has a team of three Chinese Singaporeans focused on analysing the Southeast Asian market and deciding upon its market-entry strategy. The firm is also talking to some Chinese education professionals to join it to help bring learning from Chinese markets.

As many as 22 members in Nykaa’s 80-people business and marketing team are those who have come back to India from the US and Europe.

But why are Indian startups more interested in hiring Indian professionals? According to these firms, the availability of such global talent is tougher and their salaries are higher. A similar talent in the US/western world coming to India would be 30-50 per cent costlier than what’s available in India.

These companies also believe that a change in the talent pool can be brought through government initiatives just like China where they have a three-year plan to dominate in AI.

A breather for the startup ecosystem hunting for top talents is that that in his budget speech in February, finance minister Arun Jaitley had announced that the government will launch a national programme on AI and doubled the budget allocation for Digital India — the government’s main initiative for promoting AI, machine learning and other innovations — to Rs 3,073 crore for this year.

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