- Build and maintain data pipelines and analytical models.

- Assist in developing machine learning models for business and risk use cases.

- Perform data cleaning, preprocessing, and exploratory data analysis (EDA).

- Create reports and dashboards for business stakeholders.

- Collaborate with Product, Business, Risk, and Engineering teams.

- Continuously improve model accuracy and data quality.

Key Responsibilities :

- Develop and deploy advanced machine learning and AI models.

- Build predictive models for credit risk, lending, collections, and customer analytics.

- Perform feature engineering, model validation, and performance monitoring.

- Translate business problems into data-driven solutions.

- Work closely with Product, Risk, Business, and Engineering teams to implement analytical solutions.

- Present insights and recommendations to senior stakeholders.

- Mentor junior data scientists and promote best practices in analytics and model development.

Required Skills :

- Strong expertise in Business Analytics and Data Science.

- Advanced proficiency in Python.

- Hands-on experience with AI/ML algorithms and model deployment.

- Strong understanding of IFRS 9 (PD, LGD, EAD, Expected Credit Loss models).

- Experience in the NBFC/Banking/Financial Services domain.

- Strong SQL skills and experience with Power BI/Tableau.

- Familiarity with cloud platforms (AWS, Azure, or GCP) is an advantage.