Associate Manager Analytics (Credit Risk)

Navi is a rapidly growing financial services company in India that offers a range of products including Personal & Home Loans, UPI, Insurance, Mutual Funds, and Gold. The mission of Navi is to provide digital-first financial solutions that are easy to use, accessible, and affordable. Leveraging our in-house AI/ML capabilities, technology, and product expertise, Navi is dedicated to creating exceptional customer experiences. As a Navi_ite, you should embody the following qualities: - Perseverance, Passion, and Commitment: Demonstrate dedication, passion for Navi's mission, and ownership by going above and beyond in your responsibilities. - Obsession with high-quality results: Consistently deliver value to customers and stakeholders by producing high-quality outcomes, ensuring excellence in all work aspects, and achieving high standards through efficient time management. - Resilience and Adaptability: Quickly adapt to new roles, responsibilities, and changing circumstances while demonstrating resilience and agility. The role involves: - Monitoring delinquent accounts to meet Company standards - Evaluating underwriting model stability and recommending policy actions to increase approval rates or reduce risk - Developing and maintaining loss forecasting models and ECL provisioning for accounting purposes - Implementing a portfolio monitoring and early warning alert system for loan book health - Utilizing data for decision-making, ensuring data accuracy, defining metrics for process improvement, and identifying areas for product and process enhancement through customer segmentation and analysis - Working with the engineering and data platform team to ensure data availability and reliability Desired Candidate Profile: - Experience in managing multiple stakeholders - Startup mindset - Team building skills - Proficiency in SQL, any BI platform (Tableau, PowerBI, Qlikview, Looker, Quicksight, etc.) - Understanding of basic statistical concepts and data platforms - Ability to identify relevant data for solving business problems and validating hypotheses - Prior experience in data modeling in R/Python and classification/regression techniques (Good to have) - Prior experience/understanding of lending/insurance/banking domain (Good to have),