Data Scientist - Business Analytics - NBFC

Model Development:

- Develop and implement predictive models using techniques such as Logistic Regression, XGBoost, Random Forest, and other advanced machine learning algorithms.

- Focus areas include Risk, Collections, and Marketing scorecards.

Scorecard Development:

Hands-on experience in building various types of credit scorecards:

- Application Scorecards (App SC)

- Behavioral Scorecards (Behavior SC)

- Fraud Detection Scorecards (Fraud SC)

Bureau Data Handling:

- Deep understanding and practical experience working with credit bureau data (e.g., CIBIL, Experian, CRIF High Mark).

- Responsible for feature extraction, data cleansing, and integration for model development.

Programming & Tools:

- Strong coding skills are mandatory in Python.

- Additional experience with SQL, PySpark, and related tools for large-scale data processing is preferred.

Domain Expertise:

- Must have prior experience working in the Banking and/or NBFC sector.

- Solid understanding of credit lifecycle, risk analytics, and regulatory requirements.

Required Skills:

- Strong proficiency in Python (mandatory), along with SQL and PySpark

- Experience with model validation, performance monitoring, and regulatory documentation

- Proven track record of working on risk modeling projects in Banking or NBFC environments

- Excellent problem-solving skills and ability to work with large, complex datasets