Team Lead Data Scientist

Strategic Oversight & Optimization Identify and scope new analytics projects by proactively engaging with business teams. Assess feasibility, impact, and resource requirements for new initiatives. New Project Scoping & Innovation Define and communicate the long-term vision for data science within the team. Develop and maintain a strategic roadmap for analytics initiatives aligned with business goals. Continuously evaluate emerging technologies and methodologies to enhance analytics maturity. Roadmap & Vision Strategically allocate resources across analytics projects based on priority, complexity, and business impact. Monitor team bandwidth and skill alignment to ensure optimal utilization and timely delivery. Identify skill gaps and initiate upskilling or hiring to strengthen analytics capabilities. Resource allocation & Team management Guide the development of predictive and prescriptive models to support new business initiatives. Ensure scalability, interpretability, and compliance of all data science solutions. Data Science Leadership Provide strategic data insights for strategic forums Collaborate with Funstion Head to identify key performance drivers and trends for budgeting exercises. Budgeting & Review Presentation Oversee the design and deployment of customer segmentation models using advanced ML techniques. Ensure alignment of segmentation insights with business strategies across channels. Monitor model performance and drive continuous improvement based on business impact metrics. Advanced Segmentation & Modelling Liaise with Function Head, zonal heads, and vertical leads to understand evolving analytical needs. Translate business requirements into actionable analytics deliverables and oversee their execution. Mentor team members to align with stakeholder expectations and ensure timely delivery of customized dashboards and reports. Stakeholder(Internal) Engagement & Customization Lead the development of claim benchmarking frameworks to identify savings opportunities across entities and claim levels. Define and standardize reporting cadence, stakeholder mapping, and report formats. Ensure quality assurance through structured review mechanisms and drive corrective actions for deviations.