Want to know if this job is worth applying to?
Bengaluru, Karnataka, India
Onsite
What You'll Do
• Own and lead complex, cross-functional insights programs from problem framing through measurable
impact.
• Build and evolve scalable data models and semantic layers that support critical business and clinical
decisions.
• Drive analytics strategy with Product, Clinical Analytics, Medical Economics, Finance, and Operations
leaders.
• Apply and champion AI-enabled workflows (for example, AI-assisted analysis and documentation) to
improve
team productivity, insight velocity, and adoption of trusted analytics practices.
• Define and enforce standards for data quality, governance, documentation, and analytics development.
• Design executive-ready dashboards and self-serve reporting experiences with clear, decision-oriented
narratives.
• Mentor and coach analysts and engineers, raising the technical bar and strengthening team delivery.
• Identify high-value opportunities to improve patient outcomes and reduce avoidable medical cost
through
hypothesis-driven analysis.
Qualifications
• 8+ years of experience in analytics engineering, BI, or data-focused analytics roles.
• Strong SQL proficiency and deep experience with cloud data warehouses (Snowflake preferred).
• Strong experience with data modeling and transformation frameworks (dbt preferred).
• Experience building and scaling dashboards in Sigma, Tableau, Power BI, or similar tools.
Demonstrated ability to lead ambiguous, high-impact work and influence cross-functional stakeholders.
• Strong analytical and problem-solving skills with attention to data quality, reproducibility, and business
impact.
• Excellent communication skills for technical and non-technical audiences, including executive
stakeholders.
• Bachelor's degree or equivalent practical experience.
Preferred Experience
• Healthcare analytics experience, especially in risk adjustment, clinical quality, utilization,
attribution, or medical economics.
• Familiarity with healthcare data structures and longitudinal/member-level analysis.
• Good to have: Python (or similar language) for automation or advanced analytics.
• Experience in fast-paced, evolving environments with high ownership and accountability.
What Success Looks Like
• Teams trust and rely on your analytics products for strategic and operational decisions.
• Insights are timely, accurate, and clearly tied to measurable business and clinical outcomes.
• Analytics assets are standardized, reusable, and easier to scale across teams.
• Team capability grows through your mentorship, technical leadership, and operating discipline.