Data Scientist- Health Policy Modeling

The Center for Health Systems and Policy Modeling at Johns Hopkins University, led by Dr. Melinda Buntin, is seeking a motivated and experienced individual to serve as our Data Scientist – Health Policy Modeling. This individual will play a key role in developing and implementing predictive models, simulation techniques, and economic analyses to address complex challenges in health care policy, spending, and delivery. This role, which will report directly to Dr. Buntin, requires robust programming experience, practical experience building and deploying models, and an interest in working on a fast-paced, growing team applying novel research approaches to issues in health policy, health care spending, and payment reform. The Center for Health Systems and Policy Modeling was founded in July 2023 under the leadership of Dr. Melinda B. Buntin, Bloomberg Distinguished Professor of Health Policy and Economics. The Center, affiliated with both the Bloomberg School of Public Health and the Carey Business School, aims to address emerging issues in health policy with rigorous empirical work with the goal of providing insights to policymakers, business, and the health care sector on how to improve health care delivery and outcomes. The ideal candidate will be eager to work as part of a team, curious about health policy, and a self-starter able to effectively communicate progress and work collaboratively. This is a hybrid role with flexible hours, requiring 2-3 days/week in person at JHU’s Washington, DC campus. Specific Duties & Responsibilities Design and develop predictive models, simulation tools, and decision support systems to analyze health care policy options. Apply mathematical optimization techniques and simulation methods to address emerging issues in health policy and spending. Validate and refine models using real-world data, sensitivity analyses, and validation studies. Leverage econometric modeling techniques to estimate the effects of changes in health care delivery and payment systems. Produce scholarly research articles for publication in academic journals. Contribute to grant proposals, research projects, and collaborative initiatives aimed at improving health care delivery and outcomes. Communicate research findings and model results effectively to stakeholders, policymakers, business leaders, and the health care sector. Mentor and provide guidance to junior team members on modeling techniques, best practices, and research methodologies. Collaborate with internal and external partners, including government agencies, industry stakeholders, and academic institutions, to leverage data resources and expand the reach of modeling research. Stay informed of advancements in modeling techniques, statistical analysis methods, and health policy research to inform ongoing projects and future directions. Minimum Qualifications Master’s Degree in Mathematics, Statistics or Computer Science or related field. Requires 5 or more years of relevant quantitative research and analytics experience. Requires 2 years of complex programming experience. Preferred Qualifications PHD Degree preferred. Experience developing and deploying predictive and prescriptive models. Practical experience with mathematical optimization problems and simulation and/or performing advanced statistical analysis. Programming experience with at least one high-level modeling system (i.e., R, Python, Julia, Mat lab, SAS). Proficiency in model validation and verification techniques. Familiarity with causal inference, longitudinal data analysis, and regression analysis. Experience generating technical reports and journal articles for peer-reviewed publication. Knowledge of databases, data structures, data processing and data mining from large enterprise transaction systems. Experience working with health care data (including, but not limited to, health insurance claims data). Experience with or knowledge of AI code generators. Familiarity with health economic concepts, including value-based payment. Demonstrated ability to mentor and train junior team members in modeling techniques and best practices. Strong presentation skills and experience communicating complex technical concepts to non-technical stakeholders. Proactive problem-solving skills, with the capacity to identify challenges, propose innovative solutions, and implement them effectively. Demonstrated ability to work independently, exercise discretion and mature judgment, and manage competing priorities at once. Classified Title: Data Scientist Job Posting Title (Working Title): Data Scientist- Health Policy Modeling Role/Level/Range: ATP/04/PH Starting Salary Range: $115,400 - $202,000 Annually ($175,000 targeted; Commensurate with experience) Employee group: Full Time Schedule: Monday to Friday: 8:30 am – 5 pm Exempt Status: Exempt Location: Hybrid/District of Columbia Department name: ​​​​​​​HPM HSPM Personnel area: School of Public Health Equal Opportunity Employer: Johns Hopkins University is an equal opportunity employer and does not discriminate on the basis of race, color, gender, religion, age, sexual orientation, national or ethnic origin, disability, marital status, veteran status, or any other occupationally irrelevant criteria. The university promotes affirmative action for minorities, women, disabled persons, and veterans.