Senior Risk Analyst - Payday Lending

Alpha Rupee; Karnataka; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

Alpha Rupee in Bengaluru (Bangalore) is seeking a Senior Risk Analyst focused on payday lending to drive portfolio insights and policy decisions. You will analyze unsecured credit data, design experiments, and translate findings into deployable risk rules.

The role requires 5+ years in data analysis, fluency in SQL and Python or R, and the ability to communicate complex results to non-analysts. You will partner with Risk, Product, and Operations to reduce delinquencies and optimize approvals.

Qualifications

• 5+ years in data analysis, with 3+ years on unsecured consumer credit portfolios.
• Experience with payday/short-tenure lending and BNPL is preferred.

Responsibilities

• Analyze loan portfolio to explain metrics like FPD7, NPL90, and approvals.
• Design and test risk experiments with defined samples and metrics.
• Maintain an experiment registry with outcomes and decisions.
• Develop risk dashboards including cohort curves, vintage and roll-rate views.
• Report findings to Risk, Product, and Operations in clear language.
• Own policy changes and BRE rule translations.
• Collaborate with BRE vendor and maintain documentation.

Skills

SQL

Python

R

Data analysis

Unsecured consumer credit portfolios

Job description

Senior Risk Analyst - Payday Lending

Function: Risk
Reports to: Head of Risk
Location: Bangalore
Type: Full-time - WFO

ROLES AND RESPONSIBILITIES

Portfolio Analysis and Experimentation

• Dig into the loan portfolio to explain what moves FPD7, NPL90, Loans per Customer, and Approval Rate.
• Run hypothesis brainstorms with the team, add your own, prioritise the list, then prove or disprove each one using data.
• Design risk and policy experiments, including sample definition, control group, success metric, and minimum runtime.
• Track every running experiment and make a decision to scale, iterate, or stop, supported by the numbers.
• Keep the experiment registry current, including hypothesis, design, dates, and measured results for every test.
• Turn findings into specific change proposals: what to change, expected metric impact, and how it will be measured.
• Own the translation of approved changes into deployable policy and BRE rules.

Policy and Rules Ownership

• Own credit policy for the product, including bureau cutoffs, affordability proxies suited to small-ticket short-tenure lending, velocity and frequency caps, repeat loan eligibility, and negative-list logic.
• Work with the BRE vendor to deploy policy changes while maintaining clear and comprehensive documentation.

Reporting and Dashboards

• Build and maintain the dashboards the Risk team relies on, including cohort curves, vintage and roll-rate views, approval funnels, and early-warning indicators specific to a 14 to 30 day bullet product.
• Monitor early delinquency indicators where Day-1 and Day-3 delinquency can be more relevant than lagging 90-DPD views.
• Deliver ad-hoc portfolio analyses for the Head of Risk.
• Present findings to Risk, Product, and Operations so that non-analysts can understand and act on them without requiring a follow-up discussion.

6 TO 12 MONTH EXPECTATIONS

• Portfolio trending toward FPD7 below 25 percent and repeat-loan retention of at least 30 percent, with clear analytical visibility into what is driving movement in both metrics.
• Maintain a live experiment registry with at least 20 completed tests, each with a measured verdict and documented decision.
• Build and document core dashboards and a query library well enough that a second Risk hire can ramp up in weeks, not months.

WHO WE ARE LOOKING FOR

• 5+ years of experience in data analysis, with 3+ years working on unsecured consumer credit portfolios. Short-tenure, small-ticket, and digital lending experience such as payday, small-ticket PL, and BNPL is strongly preferred over long-tenure secured lending backgrounds.
• Deep understanding of risk metrics and their P and L impact, including FPD7, NPL90, roll rates, and risk-adjusted yield.
• Hands-on experience with SQL and Python or R, with the ability to write your own queries and scripts against raw loan-level data without dependency on others.
• Ability to demonstrate a hypothesis you formed, tested, and translated into a change that moved a portfolio metric.
• Advanced daily use of AI tools for drafting and stress-testing queries, reasoning through analyses, and producing clear, readable reports.
• Ability to explain complex analysis to non-analysts in one pass without simplifying away the key conclusion.
• Track record of identifying problems that were not explicitly assigned to you and bringing data-driven evidence to prove them.
• Fluent English, both written and spoken.