Data Science Manager – Portfolio Analytics

About the role

The Data Science Manager will work closely with the client’s analytics team to drive growth across the BFSI domain. You will lead the design and deployment of predictive analytics, portfolio optimisation, and machine‑learning solutions that enhance card activation, customer engagement and spend behaviour.

Key responsibilities

• Develop predictive models such as customer segmentation, look‑alike, persona‑based targeting and merchant targeting frameworks.
• Identify actionable insights to improve card activation, portfolio growth and spend patterns.
• Design analytical frameworks to increase card spend across channels, categories and corridors.
• Build, validate and deploy large‑scale machine‑learning models using XGBoost, classification and propensity algorithms.
• Perform advanced feature engineering, model optimisation and continuous performance monitoring.
• Translate business challenges into analytical problem statements and data‑driven strategies.
• Manage end‑to‑end data‑science projects, including planning, execution, governance and stakeholder communication.
• Present findings and recommendations to both technical and non‑technical audiences.

Required profile

• 10–13 years of experience in Data Science and Analytics.
• At least 4 years in BFSI, banking, payments, cards or financial services.
• Proven track record in portfolio and customer analytics.

Required skills

• Python (Pandas, NumPy, Scikit‑learn).
• SQL.
• XGBoost (mandatory) and other classification/propensity modelling techniques.
• Jupyter Notebook and Python development environments.
• Data‑visualisation and reporting tools.