Data Scientist — Credit Modeling (product)

Experience: 2–5 years Background: Data science with credit risk exposure at / with an NBFC or bank Location: Remote Type: Full-time About the role We're a product company building credit modeling capabilities for the lending ecosystem.

We work closely with NBFCs to turn credit risk modeling into a robust, reusable product — not one-off models, but a platform that lenders can rely on.

We're looking for a Data Scientist who understands how credit models are actually built and governed inside NBFCs, and who wants to translate that domain knowledge into a product.

You'll sit at the intersection of data science, credit domain expertise, and product engineering.

What you'll do Design and build credit modeling capabilities into our product — scorecards, PD/LGD/EAD, behavioral and collections models — as reusable, configurable components rather than bespoke one-offs Encode real NBFC credit workflows (Wo E/IV binning, segmentation, reject inference, calibration, monitoring) into the product so it reflects how lenders actually work Partner with NBFC stakeholders to understand their modeling and governance needs, and translate those into product requirements Build pipelines that ingest bureau data (CIBIL, Experian, Equifax, CRIF), transaction data, and alternate data in a generalizable way Design model monitoring and explainability into the product (KS, Gini, PSI, SHAP) so it's defensible under RBI / regulatory expectations Work with product and engineering to ship features, not just notebooks What we're looking for 2–5 years in data science, with hands-on credit risk modeling at or with an NBFC / bank Understanding of the end-to-end credit modeling lifecycle and how it's governed in regulated lending Strong Python and SQL; comfort writing production-quality code, not just exploratory notebooks Familiarity with bureau data and the Indian lending landscape A product mindset — you think about reusability, configurability, and how a model becomes a feature other people rely on Good to have Experience taking models to production (APIs, pipelines, deployment) Exposure to model governance / validation / RBI guidelines on credit models Familiarity with scorecard tooling (Opt Binning, scorecardpy) and interpretability (SHAP, Interpret ML) Prior experience in a product or platform team, or building tools used by others How to Apply Interested candidates can apply through Linked In or send their resume along with Git Hub profile or project links to: Candidates with personal coding projects, AI experiments, or open-source contributions are highly encouraged to apply.