About this role
Experian seeks a Senior Risk Analyst – Data Science & Analytics for its Commercial Bureau Analytics & Pre-Sales Consulting team, focused on MSME bureau analytics. Based on-site in Mumbai and reporting to a Senior Analytics Consultant, the role combines hands-on credit-risk modelling with client solutioning and guidance of other analysts. It supports banks, NBFCs, fintechs and other MSME lenders.
Responsibilities
- Lead bureau analytics engagements across acquisition, underwriting, segmentation, portfolio monitoring, early warning and collections, from problem definition through validation and delivery.
- Define outcomes and bads, observation and performance windows, samples, segmentation, class-imbalance treatments, benchmarks and validation plans. Engineer entity-level variables from business and facility/tradeline histories, including repayment, delinquency, exposure, utilisation, enquiries and changes in credit behaviour.
- Develop and validate interpretable MSME scorecards and predictive models against machine-learning challengers, weighing predictive performance against stability, explainability and implementation. Conduct vintage, cohort, roll-rate, migration, concentration and delinquency analyses; quantify bureau data’s incremental value through benchmarks and proofs of concept.
- Lead client discovery and pre-sales discussions, scope solutions, present methodologies and translate results into credit-risk recommendations. Develop reusable features and frameworks with Product and Technology teams, including UAT, implementation and monitoring needs. Review analysts’ code and methods, mentor colleagues and meet security, governance, documentation and compliance requirements.
Requirements
Approximately 5–8 years in credit-risk analytics, data science, decision science or statistical modelling, including at least 3 years of substantial MSME, SME or commercial credit-risk or bureau analytics experience. Advanced Python and strong SQL are required, along with end-to-end scorecard ownership, commercial bureau-data expertise and experience with lender clients. Required modelling knowledge includes binning, WoE/IV, logistic regression, variable selection, calibration, segmentation, score scaling and tree-based or gradient-boosting challengers; validation knowledge includes KS, Gini/AUC, lift, back-testing and stability monitoring. Client-facing, pre-sales, code-review and coaching capabilities are also required.
Preferred
Commercial bureau score development; experience across MSME products and lifecycle stages; SAS, Git, Spark or Databricks; production deployment and challenger monitoring; knowledge of Indian lending governance and regulatory expectations; and development of reusable analytical solutions.
Benefits include a discretionary bonus, pension, health and term life insurance, Sharesave, 25 days’ annual leave, 13 bank holidays and three volunteering days. Additional annual leave can be purchased.