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Location
Noida/Nagpur
Employment Type
Experienced Professionals
Experience Level
10+
Education
Master's/PhD in Stat, CS/ B.Tech /EcoRole Summary
We are looking for a Director, Modeling and Data Science to lead the machine learning and statistical models behind our lending and deposit products, including credit risk, fraud, collections, pricing, and marketing. You will lead a team of experienced data scientists and set the direction for how client organization builds models that are accurate, interpretable, and compliant. You will work closely with partners across Risk, Technology, Marketing, and Compliance to turn those models into better decisions for the business and our members.
Job Description
Lead the end-to-end lifecycle of machine learning and statistical models, from development and deployment through monitoring and retraining, across credit, fraud, collections, pricing, and marketing decisioning
Set the modeling roadmap and priorities for the function, balancing business impact, regulatory expectations, and team capacity
Build, manage, and mentor a team of data scientists and machine learning experts, holding a high bar for technical rigor and accountability
Partner with Credit Strategy, Marketing, Risk, Engineering, Model Risk Management, and Compliance to align solutions with business goals, and explain complex technical concepts clearly to executives and oversight functions
Apply advanced techniques such as gradient boosting, deep learning, and ensemble modeling to improve model performance
Shape Happen Bank's ML infrastructure and tooling for scalable experimentation and deployment, and identify new data sources that improve model performance
Ensure rigorous documentation, governance, and validation in line with financial services regulatory requirements, including model risk and fair lending expectations
Embed AI into how the team works, using it to speed up development, analysis, and documentation while keeping human oversight, data integrity, and accountability in place
Key Skills
- 10+ years of experience in machine learning, data science, or credit risk analytics, preferably in consumer lending or financial services, including 6+ years in people management; bachelor's degree in a related field; or equivalent work experience
- You lead the team with clear direction and sharp accountability, and you make sound calls on priorities, tradeoffs, and risk
- You have strong technical depth in supervised and unsupervised learning (e.g., logistic regression, decision trees, GBMs, neural networks) and are proficient in Python and key ML libraries (e.g., Scikit-learn, XGBoost, TensorFlow, PyTorch)
- You have a deep understanding of the model lifecycle, from development through monitoring and retraining
- You are familiar with model governance practices and regulatory frameworks (e.g., SR 11-7, OCC guidance)
- You understand how AI and ML models interact with credit risk decision-making, including their limitations, failure modes, and regulatory implications, and you know when a model should inform a decision versus drive it
- You have a clear perspective on where AI adds real leverage across your function and have turned it into how your teams operate, fostering a culture of innovation while keeping accountability sharp
- You have a proven record of delivering complex, cross-functional projects, managing stakeholder expectations, and bringing partners along as the work evolves
- Hands-on experience developing LLM and foundation models, such as transformer-based sequence models, pre-trained tabular models
Benefits
- Well-being Leave: Prioritize mental wellness with the opportunity to attend a 10-day Vipassana meditation course.
- Birthday Leave: Celebrate your special day with a well-deserved day off.
- Flexible Timings: Enjoy flexibility that supports work-life balance.
- Referral Bonus: Earn rewards for successful employee referrals.
- Health & Insurance Benefits: Access subsidised insurance coverage and annual health check-ups.
- Professional Development: Grow your skills through learning and development opportunities.