WE ARE HIRING

Credit Risk and Analytics Expert

Uni is looking for a hands-on Credit Risk and Analytics Expert to improve customer evaluation, acquisition, and portfolio outcomes across cards and other lending products. The role combines modelling and bureau-data expertise with an understanding of growth, customer value, and P&L. You will turn analysis into practical recommendations with product, growth, risk, and lending partners.

What You Will Do:

- Analyze credit and acquisition performance by customer segment, channel, approval outcome, and cohort; identify opportunities to improve underwriting and customer experience.

- Build and validate hands-on predictive models and features for customer evaluation, acquisition, propensity, engagement, and retention; monitor performance after launch.

- Use credit bureau reports, variables, and trends to strengthen models and customer evaluation; assess data quality and incremental value.

- Understand portfolio composition, utilization, customer behaviour, and performance trends across cards and other lending products.

- Work with bank and lending partners to evaluate policy outcomes and recommend targeted underwriting or line-assignment refinements based on evidence.

- Lead growth and customer value management analysis across conversion funnels, activation, usage, cross-sell, retention, offers, and lifecycle journeys.

- Design experiments and challenger analyses; forecast acquisition, engagement, and portfolio outcomes and quantify trade-offs among growth, risk, and profitability.

- Connect findings to P&L drivers such as revenue, acquisition and servicing costs, contribution margin, customer lifetime value, and unit economics.

- Explore AI and machine-learning use cases in analytics and decision support with appropriate validation and explainability.

- Define metrics, automate recurring reporting, communicate actionable insights, and guide junior analysts.

What You Bring:

- Bachelor's degree from a Tier-1 college (IIT, BITS, NIT) or an equivalent quantitative background.

- 5 - 6 years of experience in credit-risk analytics, data science, or quantitative modelling for cards or other lending products, including hands-on model development.

- Strong understanding of credit bureau data, underwriting concepts, and portfolio analytics, alongside exposure to growth and customer value management problems.

- Proficiency in Python and SQL, statistical analysis, experimentation, forecasting, and visualization tools such as Tableau, Domo, or Power BI.

- Understanding of P&L and unit economics and exposure to AI/ML applications.

- Ability to guide junior team members and drive cross-functional analytical projects to completion.