<p>Job Summary</p> <p>A physician-health policy researcher in the Department of Internal Medicine, Division of General Medicine, seeks a full-time Statistician Senior (underfill to Intermediate) to join a dynamic, interdisciplinary research team. Our team performs health economics research to better understand and develop policies to lower health care spending and improve healthcare delivery and patient outcomes. Core topic areas include the effects of corporate ownership and market structure on system outcomes and how payment reform is reshaping U.S. primary care. We use large national datasets and advanced statistical (econometric) methods to generate evidence that informs health policy and clinical practice.</p> <p>The successful candidate will manage, clean, and analyze administrative datasets (e.g., Medicare claims, prescribing, and corporate ownership data); write reproducible code in Stata, SAS, R, or Python; and contribute to study design, statistical modeling, and publication. We are seeking a statistician who is curious, detail-oriented, and motivated by policy-relevant questions, able to work both independently and collaboratively across institutions.</p> <p>The position is based at the University of Michigan (U-M) and will involve close collaboration with Brown University Center for Advancing Health Policy through Research (CAHPR), led by a health economist faculty PI. The candidate will be financially supported by both U-M and Brown University (approximately 50/50) but will hold an employment relationship only at U-M. The candidate will have the opportunity for deep collaborations across Michigan Medicine, U-Ms Institute for Healthcare Policy and Innovation, and Brown University CAHPR, offering a rich environment for interdisciplinary research with leading economists and health policy scholars. The position offers outstanding professional growth, including opportunities for skill development, mentorship, and authorship on peer-reviewed papers.</p> <p>Mission Statement</p> <p>Michigan Medicine improves the health of patients, populations and communities through excellence in education, patient care, community service, research and technology development, and through leadership activities in Michigan, nationally and internationally. Our mission is guided by our Strategic Principles and has three critical components; patient care, education and research that together enhance our contribution to society.</p> <p>Why Join Michigan Medicine?</p> <p>Michigan Medicine is one of the largest health care complexes in the world and has been the site of many groundbreaking medical and technological advancements since the opening of the U-M Medical School in 1850. Michigan Medicine is comprised of over 30,000 employees and our vision is to attract, inspire, and develop outstanding people in medicine, sciences, and healthcare to become one of the world?s most distinguished academic health systems. In some way, great or small, every person here helps to advance this world-class institution. Work at Michigan Medicine and become a victor for the greater good.</p> <p>What Benefits can you Look Forward to?</p> <ul> <li>Excellent medical, dental and vision coverage effective on your very first day </li><li>2:1 Match on retirement savings </li></ul> <p>Responsibilities*</p> <ol> <li>Data management </li></ol> <p>Supporting Actions: Clean, organize, and link large administrative datasets (e.g., Medicare claims, prescribing data, and corporate ownership data) from multiple sources. Develop and maintain reproducible data pipelines and documentation to ensure transparency and data integrity. Conduct quality assurance procedures, including audits, validation checks, and version control. Assess data quality and completeness, address data limitations, and prepare analytic files for use by research teams. Ensure all datasets meet standards for reproducibility and documentation required for publication and data sharing.</p> <ol start="2"> <li>Statistical analysis and visualization </li></ol> <p>Supporting Actions: Conduct descriptive and inferential analyses to answer policy-relevant research questions. Apply econometric and causal-inference methods (e.g., difference-in-differences, instrumental variables, propensity-score methods) and selected machine-learning algorithms. Write reproducible code in Stata, R, SAS, or Python; summarize and interpret results for manuscripts, presentations, and grant proposals; and contribute to the development of statistical models and study design. Generate clear, publication-quality visualizations and tables that communicate analytic findings to technical and policy audiences.</p> <ol start="3"> <li>Assist with writing papers and grant proposals </li></ol> <p>Supporting Actions: Draft and refine statistical methods and results sections for manuscripts and grant proposals. Interpret and summarize analytic findings for publication and presentation. Prepare reports for internal and external review committees. Participate in manuscript development for peer-reviewed journals and proposal writing, particularly those sections related to study design, analytic approach, and data sources. Provide pre-award analytic support to projects, such as conducting preliminary analyses and synthesizing results. Engage in departmental and cross-institution research seminars and workshops. Co-authorship is available for substantive contributions.</p> <ol start="4"> <li>Supervise and/or mentor trainees </li></ol> <p>Supporting Actions: Supervise and/or mentor students and trainees, consult on methodological and statistical issues, and provide analytic and technical support as needed. Provide guidance on study design, analytic planning (including power calculations, model selection, and sample size estimation), and preparing presentations and publication-quality manuscripts. Collaborate closely with faculty and analysts to ensure analytic accuracy and reproducibility across projects.</p> <p>Required Qualifications*</p> <p>Senior Level</p> <ul> <li>Masters degree in relevant field, per below. </li><li>Three or more years of experience in data management and statistical analysis </li></ul> <p>Intermediate Level</p> <ul> <li>Bachelors degree in relevant field, per below. </li><li>One or more years of experience in data management and statistical analysis. </li></ul> <p>Both</p> <ul> <li>Degree in statistics, biostatistics, economics, health services research, public health, public policy, data science, computer science, or a related field focused on data analysis and interpretation. </li><li>Proficiency with one or more statistical software packages (Stata, R, Python, or SAS). </li><li>Demonstrated ability to apply regression and descriptive analytic techniques to quantitative data. </li><li>Strong organizational, analytical, and written communication skills, with close attention to detail. </li><li>Ability to work independently and collaboratively across multiple projects and deadlines </li></ul> <p>Desired Qualifications*</p> <ul> <li>Experience analyzing and managing large, complex datasets, including health care claims (Medicare and/or commercial) or electronic health record data </li><li>Experience applying causal-inference and econometric methods (e.g., difference-in-differences, instrumental variables, propensity score methods). </li><li>Experience with machine learning algorithms or predictive modeling. </li><li>Experience preparing analytic code, documentation, and supporting materials for publication. </li><li>Ability to produce clear analytical documentation and visual presentations of statistical results (charts, tables, and other visual aids). </li><li>Familiarity with longitudinal data analysis, methods for handling missing data, and resampling techniques such as bootstrapping. </li><li>Knowledge of the U.S. health care system and health policy context. </li><li>Training or experience mentoring students or junior analysts. </li></ul> <p>Work Schedule</p> <p>This position is based at the North Campus Research Complex (NCRC) in Ann Arbor and offers a hybrid work schedule with regular on-site presence expected. Fully remote arrangements are not available.</p> <p>Modes of Work</p> <p>Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes</p>