Credit Data Scientist (Credit Analytics) - Bengaluru
Core
Use data, feature engineering, and experimentation to improve credit decisioning and portfolio performance across lending products.
Role type
Credit Data Scientist
Builds
Production-aligned features, predictive models, and monitoring systems for credit risk.
Domain
Financial Services / Credit Risk
Deliverable
production ML models
Required skills
Python, SQL, statistics, predictive model evaluation, machine learning (ensemble methods, cross-validation), feature engineering, data quality assessment
Preferred skills
bureau data analysis, open banking/transactional data, device/behavioural signals, cloud analytics stacks (BigQuery/Snowflake/Databricks), Git
Technologies
Python, R, SQL, BigQuery, Snowflake, Databricks, Git
Responsibilities
Analyse customer, bureau, transactional, and repayment data to identify risk drivers; Build and iterate credit risk features and model inputs; Design, run, and evaluate credit policy experiments; Develop monitoring for model/policy performance and feature health; Support portfolio analytics (vintage analysis, roll-rates, migration, loss driver deep-dives); Work with Data/Engineering to improve data definitions, quality, and reproducible pipelines.
Seniority
Mid-level (2–4 years experience)
