Role & responsibilities
Build and maintain ETL and feature-engineering pipelines using PySpark on Databricks
Work on bureau + banking/alternate datasets to create credit risk and fraud features
Develop ML based predictive models for Credit risk (e.g. Application scorecard, Behavioral Scorecard)
Deploy models using Quick API/Flask as production APIs on cloud
Perform model validation and monitoring using PSI, CSI, KS, GINI, AUC-ROC and decile analysis
Communicate analytical insights and actionable recommendations to policy stakeholders.
Support scorecard/model documentation, model governance and submission activities
Stakeholder engagement for requirement gathering and delivery of projects
Ad hoc analytical activities

Preferred candidate profile
Technical Skills:



Must have Solid Python(Pandas, Scikit-Learn), SQL, PySpark + Databricks
Must have Scorecard development Skills: WOE, IV, Logistic Regression, Reject Inferencing, Machine learning Algorithms (XGBoost, Random Forest, LightGBM etc)
Model deployment: FastAPI or Flask
Candidates must have min 3+ years of hands-on experience in Credit risk analytics and Scorecards development.
Candidate must have worked in Bank/NBFC/Fintech/Credit bureaus
Qualification: M.Sc. Statistics, B.Tech., MA Economics, MBA
Positive to have skills: Git,CICD,Tableau

📌 Credit Analyst Pune
🏢 SKILLVENTORY
📍 Pune