Manager, Data Analytics

Opportunity Overview: We are seeking a Technical, Hands-on Manager to lead a team responsible for building and maintaining high-quality healthcare market datasets and analytics that power internal insights, benchmarking, and external thought leadership . In this role, you will lead a team of data analysts responsible for the development, quality assurance, and ongoing refresh of market data assets. You will combine strong people leadership with technical expertise in analytics and data science to ensure reliable, scalable data pipelines and actionable insights. The ideal candidate is both a strong people manager and a hands-on analytics leader who can guide analysts in rigorous data methodology, translate data outputs into meaningful business insights, and partner closely with commercial strategy, product, clinical, and analytics stakeholders. What you’ll do: Lead and develop a team of data analysts responsible for the creation, validation, and ongoing refresh of healthcare market datasets. Mentor analysts in data methodology, statistical reasoning, and reproducible analytics practices to ensure consistent and rigorous analysis across the team. Establish analytic standards, coding practices, and documentation expectations to ensure all datasets and insights produced by the team are reproducible and scalable. Establish and maintain governance processes for market data including versioning, documentation, auditability, and traceability of data sources and methodologies. Oversee change-detection logic, ensuring the team systematically identifies and documents additions, removals, and shifts in the market dataset. Define and enforce data quality standards across ingestion, transformation, and analysis workflows. Collaborate with Data Engineering and Platform teams to ensure the underlying data infrastructure supports scalable ingestion, transformation, and analytics workflows used by the analyst team. Translate analytic outputs into business insights, benchmarks, and structured datasets that support product strategy, commercial enablement, and thought leadership initiatives. Drive the implementation of project scope definition, effort estimation, and planning in close coordination with cross-functional teams. Conduct code reviews and analytics methodology reviews to ensure maintainable, reproducible data workflows and high-quality analytic outputs. What you’ll need: Must-haves 7+ years of professional experience in data analytics, data science, or quantitative analysis in a production environment. Strong proficiency in Python and data analysis libraries (Pandas, NumPy, SciPy, Matplotlib). Advanced SQL querying and ability to work with large datasets. Strong understanding of statistics, data analysis methods, and pattern detection in complex datasets. Experience managing multiple concurrent analytics projects and prioritizing work across a team of analysts. Experience designing analytic frameworks or benchmark datasets used by business teams or external stakeholders. Experience managing data quality, data governance, and dataset lifecycle management. Experience evaluating and applying modern analytics or AI techniques (including LLM-based tools where appropriate) to enrich datasets or accelerate analytic workflows. Experiment and rapidly prototype design frameworks and validate hypotheses efficiently. Strong software engineering fundamentals including modular Python code, reusable analytic functions, and maintainable data pipelines. Familiarity with cloud data platforms (e.g., AWS, GCP, or Azure) and common data services used to store, process, and query large datasets. Work seamlessly across Data Science, Engineering, Product, DevOps, and Data Engineering teams to align technical decisions with business goals, ensuring smooth integration of AI/ML capabilities into production systems Excellent communication and storytelling skills, capable of translating complex AI/ML concepts into clear, actionable insights for leadership, stakeholders, and non-technical partners. Ownership mindset with end‑to‑end accountability, ensuring delivery from concept to deployment to monitoring—while continuously identifying risks, blockers, and opportunities for improvement. Nice-to-haves Background in healthcare payment integrity, clinical data workflows, or payer/provider analytics. Thought leadership in analytics-driven market intelligence, benchmarking, or healthcare data insights. Experience working with healthcare claims, authorization, or utilization management data. Experience producing market intelligence, benchmarking studies, or industry datasets. Familiarity with healthcare payer workflows or healthcare analytics environments. Familiarity with compliance, governance, and security best practices for healthcare data (HIPAA, PHI handling, logging, auditing). Ability to commute/relocate: Nacharam, Hyderabad, Telangana*: Reliably commute or planning to reloc