Data Scientist 2-Digital Banking

Data Scientist 2-Digital Banking Kotak 811-Regional Sales

About Us: Kotak811 is a completely digital, in-your-phone, mobile bank. It was founded in 2016 to help India adapt, evolve, and eventually overcome the barrier of digital banking and make it accessible to all. Our sole aim is to bring you the excitement and ease of digital banking with the trust and reassurance of Kotak Mahindra Bank’s experience and legacy. Incubated by Kotak Mahindra Bank, Kotak811 is where innovation meets banking to offer the user the most seamless banking experience there has ever been. (Kotak 811 is a digital zero balance savings account that can be opened online by everyone (Indian residents only) which acts as a one-stop solution for all your financial needs and day to-day transactions.) Equal Employment Opportunity: All employment decisions shall be made without regard to age, race, creed, colour, religion, sex, national origin, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by the state, or local law. Kotak 811, is committed to providing equal employment opportunities Role: Data Scientist 2 Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 1- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 2- Have worked across end to end in model design, development, validation, documentation & deployment. 3- Create great data stories with expertise in robust EDA and statistical inference