As a Data Science & Portfolio Analytics Professional, you will work directly with the client’s analytics team to leverage data science, predictive analytics, portfolio management analytics, customer segmentation, and machine learning. Your work will drive business growth, customer engagement, card activation, spend enhancement, and portfolio optimisation across the BFSI domain.
What You’ll Do and How You’ll Succeed
Portfolio Analytics & Data Science
- Develop predictive analytics solutions including customer segmentation models, lookalike models, persona‑based targeting frameworks, and merchant targeting strategies.
- Identify actionable business insights to improve card activation, customer engagement, portfolio growth, and spend behaviour.
- Design and implement analytical frameworks to increase customer card spends across channels, categories, and corridors.
- Analyse customer portfolios and provide recommendations to optimise business performance.
Machine Learning & Modeling
- Build, validate, and deploy predictive models using large‑scale datasets.
- Perform advanced feature engineering and model optimisation.
- Develop machine learning models using algorithms such as XGBoost, classification models, segmentation models, and propensity models.
- Monitor and improve model performance through continuous evaluation and refinement.
Business Consulting & Strategy
- Understand client business challenges and translate them into analytical problem statements.
- Develop data‑driven frameworks aligned with business growth strategies.
- Provide recommendations to stakeholders based on analytical findings and model outputs.
- Support decision‑making through quantitative insights and predictive analytics.
Project Management & Stakeholder Engagement
- Manage end‑to‑end data science projects from problem definition through deployment.
- Drive project planning, execution, monitoring, and governance.
- Collaborate with stakeholders across product, operations, business, and analytics teams.
- Provide regular project updates and ensure transparent communication throughout the project lifecycle.
- Present findings and recommendations to both technical and non‑technical stakeholders.
We’d Love to Hear From You If…
Experience
- You have 10–13 years of overall experience in Data Science and Analytics.
- You have at least 4 years of experience in BFSI, Banking, Payments, Cards, or Financial Services.
- You have proven experience in portfolio analytics and customer analytics.
Technical Expertise
- You are proficient in Python (Pandas, NumPy, Scikit‑learn) and SQL.
- You have experience working with large datasets and data manipulation techniques.
- You are skilled in machine learning techniques including customer segmentation, lookalike modelling, predictive modelling, feature engineering, and model validation.
- You have strong expertise in XGBoost (mandatory), classification, and propensity models.
- You are experienced with Jupyter Notebook, Python environments, and data visualisation/reporting tools.
Ways of Working
- You demonstrate strong analytical and problem‑solving skills.
- You bring business acumen and strategic thinking to data science projects.
- You manage stakeholders effectively and communicate insights clearly.
- You take ownership of project delivery and governance.
- You collaborate cross‑functionally to align analytics with business goals.
- You convert data insights into actionable business strategies.