Source – https://www.analyticsinsight.net/
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.