Head of Patient Data, Epidemiology and Patient Data Products

As Head of Patient Data, you will lead our groundbreaking patient data platform that is revolutionizing drug discovery. Our innovative platform leverages advanced computational techniques to accelerate the development of new medicines. You will lead a team of data scientists, data engineers, and informaticists at the intersection of AI capability innovation and implementing machine learning tools to solve real patient problems that have significant impacts on global health. You will own the team’s strategic vision and collaborate with epidemiology machine learning, product engineers, and business innovation leaders to align product initiatives with patient needs. 

A successful candidate is passionate about leading high-impact teams, navigates ambiguous problems--right-sizing complex computational tasks, and delivers innovative machine learning/AI-enabled patient data products to internal stakeholders, for direct application in external partnerships, on time. 

What You’ll Do… 

• Elevate Patient perspective in Drug Discovery and Development: Ensure Valo’s real-world data (RWD) platform is optimally positioned for teams to extract actionable insights, directly influence drug discovery and development programs, while supporting platform scalability and expansion. 
  • Champion the Valo RWD user experience: responsible for integration, adoption, and uptake of Valo’s electronic health record data and RWD platform across Valo computational teams. Develop rapid and robust user onboarding to data assets embedded in engineered pipelines and tools developed for specific projects.
  • Improve patient representation AI in RWD workflows (eg, feature engineering, data curation, fit-for-purpose tooling). Build from common data models that enable fluid integration across data assets. 
• Lead Patient Data Asset Platform: Develop and execute Valo’s platform strategy, ensuring alignment with overall organizational goals, while working closely with software and infrastructure engineers, epidemiology and data science leaders, and drug discovery researchers.
  • Own RWD tooling roadmap to unlock RWD capabilities for maximal impact. Collaborate with teams to build scalable real-world evidence products that accelerate insight generation, for existing partnerships, and generate new entry points for RWD in business development.
  • Partner with epidemiology and data science leaders to execute continuous evaluation of RWD data assets. Develop automated systems to validate/QC data processing for existing and prospective RWD vendors. Systematically evolve patient feature mapping and standardization across RWD sources. 
• Lead high-performing team: Responsible for developing team roadmap, mentoring, and career development of a multidisciplinary clinical informatics, data science, and data engineering group. Foster a culture of excellence dedicated to scientific rigor and continuous learning while contributing to Valo’s broader goal of being recognized externally for cultural excellence. 

What You Bring… 

• Technical Product leadership: Demonstrated experience building scalable data pipelines and technical infrastructure to support clinical or RWD tools for commercial use, including machine learning/AI-enabled products.
• Hands-On Patient Data Experience: Proven experience with RWD, electronic medical records, or patient registry data, generating insights and actionable recommendations.
• Leadership and Management Skills: Track record of successfully leading high-performing teams, promoting collaboration, and achieving strategic goals.
• Excellent Communication: Exceptional oral and written communication skills, adept at presenting complex information clearly to diverse audiences.
• Strategic Thinker: Ability to translate scientific insights into actionable business strategies.
• Passion for Innovation: Strong drive to innovate and advance RWD research and development practices. Experience identifying and executing value-creating opportunities in health tech/pharmaceutical domain 

Nice to have… 

• Experience with U.S. and non-US healthcare datasets, healthcare systems, and administrative data (e.g., billing claims, pharmacy data).
• Strong computational background, hands-on experience in applying causal inference approaches in observational data.
• Prior experience with leading data-driven research and data-as-a-product in a commercial setting.
• Familiarity with real world evidence approaches in drug discovery