Role Overview:

Are you a hands-on Data Science & Analytics specialist who loves digging into complex financial or insurance datasets to drive real-world business impact?

We are seeking an Analytics Lead to drive data-driven decision-making across our core business functionsincluding Claims, Underwriting, Sales, Customer Experience, and Risk. This role combines 90% hands-on modeling and analytics execution with 10% business partnering and stakeholder management.

If you have a strong foundation in SQL, Python, and Classical Machine Learning across the BFSI (Banking, Financial Services, and Insurance) or Health Insurance domainand know how to take projects from problem definition all the way to production deploymentwe want to talk to you!

Key Responsibilities:

1. Hands-On Data Science & Machine Learning (90%):

- Predictive Modeling: Build, validate, deploy, and monitor classical machine learning models for churn prediction, claims propensity, fraud detection, risk segmentation, customer lifetime value (CLTV), and lead scoring.

- End-to-End Pipeline Ownership: Perform feature engineering, hyperparameter tuning, model performance optimization, and statistical testing on complex datasets.

- Production Deployment: Partner closely with Data Engineering and IT teams to productionize models and integrate insights into business workflows.

- BI & Reporting: Design actionable dashboards and reporting frameworks using Power BI or Tableau with clean SQL-driven data pipelines.

- Data Quality & Governance: Work with large-scale data from policy administration, claims, CRM, digital, and third-party sources while enforcing data validation standards.

2. Business Partnering & Stakeholder Engagement (10%):

- Problem Translation: Partner with business leaders across Claims, Underwriting, Risk, and Sales to convert complex business challenges into clear analytical roadmaps.

- Executive Presentations: Synthesize complex ML outputs into clear, actionable business recommendations for senior stakeholders.

- Impact Tracking: Monitor, quantify, and report on the financial and operational impact of deployed analytics initiatives.

- Team Leadership: Manage small analytics project tracks, mentor junior team members, and ensure delivery excellence.

Required Skills & Qualifications:

Domain & Experience:

- 7 to 10 Years Total Experience in Data Analytics and Data Science.

- Proven BFSI / Health Insurance Background: Hands-on experience solving domain problems across Claims, Fraud Analytics, Underwriting, Risk, or Customer Retention.

- Project Ownership: Track record of managing end-to-end analytics initiatives from initial scoping to technical implementation.

Technical Skill Set:

- Advanced SQL: Expert-level query optimization, complex joins, and window functions across large-scale relational databases.

- Python / R: Deep technical fluency in data processing (pandas, numpy) and classical ML libraries (scikit-learn, xgboost, lightgbm, statsmodels).

- Classical Machine Learning & Statistics: Deep expertise in regression, decision trees, random forests, gradient boosting, clustering, and hypothesis testing.

- BI & Visualization: Proficiency in Power BI or Tableau and Advanced Excel for data storytelling.

Educational Qualification:

- B.Tech / B.E. / B.Sc. in Computer Science, Statistics, Mathematics, or a related quantitative field.