Senior Manager, Data Science

Job Description

Youll lead the Data Science function supporting Lending, overseeing credit risk scoring models across PD, LGD, and collections. Youll guide the team in leveraging alternative data to improve model accuracy and signal. Youll lead the full model lifecycle driving strategy, standards, and execution across model development, validation, deployment, and monitoring. Youll partner with business, risk, and ops leaders to shape the credit roadmap and influence decisions with data-driven insights. You are experienced in leading teams while being hands-on when needed. This role is suited for professionals with 10+ years of experience in data science and risk analytics. This role is onsite based in Bangalore. The Critical Tasks You Will Perform Lead the team in building predictive models to separate good vs bad borrowers using ML and traditional methods Drive development of ML and deep learning models for loss estimation across portfolios Oversee model validation and performance monitoring across diverse data sets Guide feature engineering strategies and explore new external data sources Champion model governance in collaboration with risk, compliance, and audit teams Ensure timely identification of performance drifts and lead model refresh cycles Communicate modeling outcomes and trade-offs to senior leadership and key stakeholders Translate analytics into strategic levers policy, pricing, targeting, and credit expansion Set the vision for solving hard data science problems using best-in-class ML techniques Read more Skills you need The Essential Skills You Need Expertise in Python for ML model development, with experience building scalable, production-grade solutions Proficient in Spark, SQL, and large-scale distributed data processing frameworks Grasp of advanced ML concepts, including model interpretability, bias mitigation, and performance optimization Experience with ML/DL libraries (scikit-learn, XGBoost, TensorFlow/PyTorch) and guiding teams on their best use Working knowledge of MLOps and orchestration tools (Airflow, MLflow, etc.), with experience standardising model deployment pipelines Exposure to LLMs and Generative AI, with a perspective on their potential applications in credit risk Ability to lead design of robust, reusable feature pipelines from structured and unstructured data sources Familiarity with Git, CI/CD, and model versioning frameworks as part of scaling DS delivery Strong problem-solving mindset and ability to coach team members through complex modeling issues With experience aligning technical outputs with business strategy