Job Description

Job Description:

This is a dual graded position posting. The grade level will be determined by the candidate's qualifications and experience.

The Senior/Lead Data Research Analyst at the School of Public Health’s Department of Health Services Policy & Practice joins a vibrant team supporting the activities of the Department and its research centers. The Senior/Lead Data Research Analyst is involved in health services and economics research to better understand and develop policies that will lower spending growth, improve patient outcomes, and drive structural change in U.S. health care delivery. Core topic areas include payment reform, long term care, the evolving landscape of Medicare and Medicare Advantage, commercial price growth, health care market structures including the impacts of consolidation and private equity ownership, and state efforts to address affordability and value.

The Senior/Lead Data Research Analyst will perform quantitative analyses for various center research projects. The analyst will use technical skills to help researchers design studies, construct databases, manage data, perform statistical programming and analysis, and interpret and report results. Much of the work will involve secondary data analysis of various administrative datasets including health care claims. The Senior/Lead Data Research Analyst will work collaboratively with faculty-led teams in a dynamic environment that encourages independent thinking, problem solving, and collegiality.

The successful candidate, as a minimum, should have the following background:

Grade 9

Bachelor’s Degree and 3 to 5 years of experience or equivalent combination of education and experience.

Grade 10

Bachelor’s Degree and 5 to 7 years experience or equivalent combination of education and experience.

Job Competencies

Demonstrated proficiency in applying various types of regression analysis, including linear, logistic, and multivariate techniques. Experience with econometric models to interpret data within an economic context

Background in propensity score matching, and causal inference models to assess treatment effects and inform policy

Experience in utilizing machine learning algorithms to analyze large datasets and generate predictive insights that support research questions

Skilled in managing and analyzing longitudinal data to track health outcomes over time and evaluate the effectiveness of interventions

Proficient in implementing bootstrapping procedures to estimate statistics on samples for robust predictive modeling

Advanced knowledge of methods to address missing data, ensuring the integrity and accuracy of analyses in the presence of incomplete data sets

Highly proficient in major statistical software package, e.g., Stata, R, SAS, Python, Tableau, Power BI

Experience analyzing and managing large complex data sets, including health care claims (commercial and/or CMS) or electronic health record data

Proficiency in descriptive analysis, modeling of data, and graphical presentations

Knowledge of the U.S. health care system

Ability to set goals and work independently to manage both short- and long-term responsibilities

Excellent organizational skills with keen attention to detail

Excellent verbal and written communication skills

Additional physical demands and working conditions:

Hybrid Eligible

All offers of employment are contingent upon a criminal background check and education verification that are satisfactory to Brown University.

This is a fixed term position with a current end date of 06/30/2028 which may be extended based upon available funding.