Lead Data Scientist - Credit Risk Modeling

Description :

Role : Lead Data Scientist Credit Risk (India)

Experience :

- 7 to 12 years in data science or analytics, with at least 45 years in credit risk / financial services / fintech / NBFC / banking.

- Proven experience deploying credit models into production environments.

- Prior leadership or mentoring experience in analytics or data science teams.

- Strong stakeholder and client-handling experience preferably involving consulting, business analytics delivery, or partner-facing projects.

- Experience in multi-geography organizations is highly desirable

What You Will Do :

Leadership & Strategy :

- Mentor and grow a small India team of data scientists and analysts; instill best practices in model development, validation, and governance.

- Partner with U.S. leadership to shape the credit analytics roadmap and prioritization.

- Lead discussions with business and partner teams to define analytical requirements and problem statements

- Communicate insights and recommendations to both business stakeholders and external partners in a clear, consultative manner.

Risk Modeling & Analytics (Technical Core) :

- Build, validate, and monitor credit risk scoring models including Probability of default (PD), Loss given Default (LGD), and Exposure at Default(EAD) frameworks.

- Develop fraud detection, early delinquency prediction, and portfolio stress-testing models.

- Design scenario analysis and simulation models to assess portfolio resiliency under different market or credit conditions.

- Partner with Data Engineering to ensure robust, scalable, and high-quality data pipelines.

Underwriting & Decision Systems :

- Collaborate with Product and Risk teams to integrate models into loan decisioning systems.

- Use external bureau, bank transaction, and alternative data to enhance model accuracy and decision transparency.

- Ensure explainability, interpretability, and regulatory compliance across all models.

- Work consultatively with lending partners or external data providers to evaluate and integrate credit innovations.

Consulting & Stakeholder Engagement :

- Act as a strategic advisor to business leaders on how analytics can drive growth, optimize risk, and improve customer experience.

- Lead data-driven storytelling sessions and synthesize complex model results into clear business narratives.

- Represent the data science function in cross-functional or external partner meetings.

What We Are Looking For :

Technical Skills :

- Deep expertise in credit risk modeling (e.g., logistic regression, decision trees, survival analysis, scorecards, machine learning for risk).

- Strong programming skills in Python and SQL; experience with MLOps tools, version control (Git), and cloud systems (AWS/GCP).

- Knowledge of bureau, bank transaction, and alternative data sources.

- Familiarity with model monitoring, governance, and explainability frameworks.