Morgan Health - Health Care Innovation, Data Science and Research Vice President

In 2021, JPMorgan Chase launched Morgan Health, a new business unit focused on improving the quality, equity, and affordability of employer-sponsored health care in the United States. Morgan Health pursues this strategy through investments, collaborations with the JPMC Benefits team, engagements with other market leaders, sophisticated data analytics and research, and policy advocacy. Morgan Health is headquartered in Washington, DC, with members of the team also based in New York City and Boston. To learn more about our strategy and latest developments, please visit: www.morganhealth.com.

As a Vice President of Data Science & Research within Morgan Health, you will utilize your deep experience with health care claims, survey data, and quality measurement to support initiatives across Morgan Health’s Innovation, Ventures, and Community Engagement teams. You will be passionate about healthcare transformation and will manage health care analytics projects throughout their life-cycle – from claims data extraction and transformation, analytics solution design, statistical analysis, data visualization, data-driven storytelling, and quantitative research outputs. You should have proven success creating and leading practical, actionable analysis plans, balancing competing priorities, and communicating their findings to both technical and non-technical stakeholders. Beyond strong analytics and communication skills, you will also be a self-motivated problem-solver who enjoys working in teams and creates value by aligning data-driven insights with business objectives. 

Job Responsibilities:

• Scope and manage complex data analytic projects end-to-end in a matrixed environment, which includes communicating with both technical and non-technical stakeholders 
• Translate business and research questions into analytics plans using JPMC’s claims data assets, and identify and implement approaches to scale or automate processes where applicable
• Become a subject matter expert on Morgan Health’s relevant data sources (including insurance claims, lab data, survey data, public data, and licensed data): understand their context and limitations, and proactively investigate and solve data quality issues 
• Collaborate with other data scientists and engineers to build well-documented, high-quality and efficient code, data architecture, and data transformations
• Carefully review and validate analytics outputs for projects across the team to ensure high levels of data quality, integrity, accurate interpretation, and adherence to HIPAA and firm-wide data use guidelines
• Keep up-to-date with industry trends in health care, data science, and artificial intelligence, and apply this knowledge in daily work

Required Qualifications, Capabilities, and Skills

• Master's degree in a quantitative field including, but not limited to statistics, engineering, math, analytics, computer science, public health, or economics
• 7 years of professional experience (or 3 years of professional experience related PhD) in hands-on analytics work, including relational database structures, data wrangling, common coding languages, and analytical and data visualization tools (e.g. SQL, Python, R; ggplot, seaborn, Tableau), including at scale (e.g., Spark)
• 5 years of health care experience, ideally in a payer, provider, or research setting that actively used claims data 
• Subject matter expertise in medical and pharmaceutical claims data, including standard groupers, common data transformations, and population health metrics
• Proven ability to successfully multitask effectively, balance competing priorities, and deliver meaningful and accurate results without supervision
• Team-oriented attitude and ability to mentor early-career health care data scientists
• Excellent verbal and written communication skills, especially when delivering analytical results to non-technical stakeholders

Preferred Qualifications, Capabilities, and Skills

• Master’s degree or PhD with a focus on health care analytics, health services/policy research, data science, statistics, or engineering
• Experience measuring quality, designing incentives, and evaluating value-based care models
• Experience with employer-sponsored insurance and employer benefits
• Experience with qualitative data methods and working with unstructured data
• Background in causal inference analysis methods and machine learning models, ideally applied in population health
• Experience building or enhancing large health care claims data warehouse environments and analytics platforms
• Peer-reviewed research outputs in fields including applied statistics, health care analytics, informatics, and medicine