Vice President Data Insights - Healthcare
Listed on 2026-05-21
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IT/Tech
Data Analyst, Business Systems/ Tech Analyst, Data Science Manager
POSITION SUMMARY
The Director / VP, Insights to Action will serve as the founding senior leader of the ITA function — responsible for both the analytical quality and the organizational build-out of a small, high-impact team. This is a player-coach role: the successful candidate will personally execute analytical work alongside three Data Scientists, maintaining deep individual contribution while also setting standards, developing team members, and managing client relationships.
The role requires an individual who combines quantitative rigor with strong communication skills and fluency in the US specialty pharmacy and pharmaceutical manufacturer ecosystem. The Director / VP will interface regularly with both internal and external stakeholders spanning market access, patient services, and commercial leadership, translating complex analytical findings into clear, actionable narratives.
KEY RESPONSIBILITIES- Lead, mentor, and develop a team of three Data Scientists; this is a player-coach role — the expectation is sustained personal analytical output alongside team management responsibilities
- Set and maintain analytical standards, review team work product, and allocate capacity across concurrent client engagements
- Contribute to hiring, onboarding, and capability development as the function scales
- Own end-to-end delivery of program analytics for assigned pharmaceutical manufacturer clients, including quarterly business review (Q ) preparation, ad hoc analyses, and ongoing insight production
- Serve as the primary analytical point of contact for senior client stakeholders; present findings to market access leaders, patient services teams, and executive sponsors
- Partner with the Commercial team on analytical content for renewals, new business proposals, and strategic account planning
- Define and maintain a standardized KPI framework for hub program performance spanning six key pre-defined families
- Lead proactive, hypothesis-driven analysis across patient throughput, stage conversion rates, payor dynamics, HCP-level behavior patterns, adherence trajectories, and financial program utilization
- Translate analytical findings into executive summaries, trend narratives, and operational recommendations formatted for manufacturer client audiences
- Collaborate with data engineering, Master Data Management (MDM), and BI architecture teams to define data requirements and ensure the analytical inputs underlying ITA are reliable, consistently defined, and properly governed
- Guide the progressive migration of validated ad hoc analyses into productized Thought Spot dashboards, contributing to the company’s long-term self-service analytics strategy
- Identify and help resolve upstream data quality and governance issues that affect insight reliability
- Support the commercial positioning of the ITA capability in coordination with Business Development leadership, including input to RFP responses, pricing discussions, and go-to-market materials
- Contribute to defining the ITA product roadmap — the progression from ad hoc delivery to a scalable, monetizable analytics offering
- 7-10 years of progressive experience in healthcare analytics, with direct and substantive experience in one or more of the following: pharmaceutical manufacturer (commercial, market access, or patient services analytics), pharma consulting, health insurer, or pharmacy benefit manager (PBM)
- Demonstrated experience managing or leading a small analytics team; player-coach orientation is essential — this role requires sustained personal contribution alongside people management
- Advanced proficiency in SQL; hands‑on experience querying and manipulating data in cloud data warehouse environments (Snowflake strongly preferred)
- Proficiency in Python or R required;
Python preferred (pandas, numpy, scipy, scikit‑learn) - Experience with Thought Spot or Power BI preferred
- Strong working knowledge of statistical methods applicable to program analytics: cohort analysis, survival analysis, funnel decomposition, regression modeling, distribution‑based performance metrics,…
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