Data Science Manager

Job Title: Data Science Manager Location: Bangalore – Bhartiya City Tech Park Experience: 8+ Years Job Type: Full-time/ Permanent Notice Period: Immediate to 30 days. Transportation: 2-way Cab will be provided General Summary: Elevate is a technology firm which develops next-generation financial products focused on managing life’s everyday expenses. The Data Science team conceptualizes, develops, deploys, and maintains predictive models using advanced statistical and machine learning methods. These models are used in Elevate’s Underwriting, Account Management, and Operations applications. Primary Responsibilities: • Manage a team of data scientists through predictive models and analytical exercises to deliver business value, innovative approaches and quality execution. • Design, Develop and Deploy advanced machine learning and Artificial Intelligence algorithms/predictive models for use in Underwriting, Customer Management, Marketing, and Operations; • Functional lead and point of contact with business partners to support the needs and goals of all Elevate portfolios, Rock teams, and Pods. • Assess, clean, merge, and analyze large datasets adhering to standardized data manipulation techniques and methodology by leveraging Python, Spark, Snowflakes, etc. • Design, Develop and Deploy linear, nonlinear, and other ML algorithms for testing, development and deployment into our underwriting engine in the application of risk management in all of Elevate’s acquisition channels; • Efficiently apply data mining methodologies to minimize credit/fraud losses, maximize response and approval rates, and develop methods to enhance profitability of Elevate products; • Successfully implement scoring models on multiple decision platforms Including cloud. • Provide knowledge, insight and guidance of third party data providers such as Transunion, Clarity/Experian and Equifax to include knowledge of products and data available, products to purchase or discontinue, cost benefit analysis of retrospective analysis, effective use of variables, data dictionaries as well as advantages and limitations; • Maintain clear, detailed model documentation on our Wiki Server by leveraging reproducible research technologies such as Jupyter Notebook, Rmarkdown, etc.