Risk Analyst

Company Description

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries.

Job Description

We are looking for a Senior Risk Analyst – Data Science & Analytics to join our Commercial Bureau Analytics & Pre-Sales Consulting team, with a dedicated focus on MSME bureau analytics. This is a senior hands-on role for an experienced credit-risk data scientist who can independently structure complex MSME lending problems, design bureau-led analytical solutions and translate modelling results into client-ready recommendations. You will lead scorecard and model development, portfolio and early-warning analytics, bureau-based proofs of concept and pre-sales solutioning for banks, NBFCs, fintechs and other MSME lenders. The role requires deep Python / SQL capability, strong credit-risk modelling judgement, substantial experience with MSME / SME or commercial bureau analytics, and the ability to guide other analysts while remaining deeply hands-on with data and code.

What you'll do

• Lead end-to-end MSME bureau analytics engagements across acquisition, underwriting, risk segmentation, portfolio monitoring, early warning and collections, from problem definition through validation and delivery.
• Own the analytical design for complex use cases, including outcome / bad definition, observation and performance windows, sample construction, segmentation, treatment of class imbalance, benchmark / challenger design and validation strategy.
• Design advanced bureau variables from longitudinal business-entity and facility / tradeline histories, including repayment behaviour, delinquency patterns, exposure and utilisation, enquiries, account vintage, product / lender mix and changes in credit behaviour over time.
• Develop, benchmark and validate MSME credit-risk scorecards and predictive models using interpretable statistical approaches and machine-learning challengers, making explicit trade-offs between predictive gain, stability, explainability and ease of implementation.
• Lead portfolio diagnostics including vintage, cohort, roll-rate, risk migration, concentration, delinquency-flow and early-warning analysis, and translate findings into actionable credit-risk recommendations.
• Quantify the incremental predictive and business value of bureau variables, scores and analytical constructs through robust benchmark and proof-of-concept designs.
• Lead client and pre-sales discussions to diagnose the problem, assess data feasibility, frame the analytical solution, scope proofs of concept, present methodology and respond to technical questions.