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Job Description
Key Accountabilities
1. Forecasting & Planning
- Develop models for balance sheet and P&L forecasting
- Build driver-based and scenario forecasting models
- Improve forecast accuracy and reduce manual adjustments
2. Profitability & Optimization
- Analyze profitability across customers, segment, product, channel
- Optimize pricing, marketing spends, and capital allocation
3. Customer & Business Decisioning
- Develop models: churn, CLTV, next-best-action, cross/upsell
- Support business teams with actionable insights
- Improve commercial effectiveness and productivity
4. Analytical Products & Automation
- Build reusable Data pipelines, ML pipelines, feature sets
- Develop dashboards and decision-support tools
- Automate reporting, analysis, insight generation
Key Relationships - Internal Stakeholders
Members of Business and Data & Analytics Division, Enabling Data & Analytics Division (IT or Data - Engineer/Governance), BAU division heads (Business, Finance, Risk, Corporate Affair, IT)
Key Relationships - External Stakeholders
Partners and vendors providing professional services
Success Profile - Qualification and Experiences
- Strong background in Data Science / ML / Quantitative Analytics
- Proficient in Python, SQL, Spark
- Experience in Forecasting (time series), Causal inference, experimentation, Model validation & explainability
- Experience with data pipelines, ML pipelines, MLOps
- Strong business translation and stakeholder management
- Clear, concise communication of insights