Senior Data Scientist

Key Responsibilities:

• Develop innovative credit risk / churn / usage models using mobile wallet transaction data, call data, telecom usage data, customer bureau data, etc.
• Partner with the Data Engineering team to define the required data pipelines to build and enhance the feature bank (foundational capability) to build/deploy the various ML algorithms both for batch and real-time use cases.
• Collaborate with credit policy/portfolio management team to drive P&L outcomes.
• Build reports for model monitoring and drive enhancements.

Required Qualifications & Skills:

• Solid expertise in end-to-end risk model lifecycle management (develop, deploy, monitor).
• Previous hands-on experience in credit, fraud, and churn model development and deployment.
• Previous experience in PD/EAD/LGD model development/validation.
• Experience in CSI/PSI model monitoring process.
• Hands-on experience in data extraction using SQL/PySpark SQL; data cleaning, feature creation, and building models using PySpark/Python on Spark; Scala will be a plus.
• Previous exposure to the below algorithms (preferably multiple): Logistic Regression, Random Forest, XGBoost, Markov Chain.
• PSI/CSI for model monitoring.
• Strategy performance tracking and swap in / swap out analysis.
• Strong entrepreneurial drive.

Must Have Skills:

• Good business understanding of the fintech/consumer finance space.
• Experience in working with credit card / personal lending space, especially fintech.
• Hands-on experience in working with telecom data.

Skills

Churn, Credit Risk, Fraud, Logistic Regression, PySpark, Python, Random Forest, SQL, XGBoost