To oversee and co-lead the Data Science and Analytics Team for the Division of Integrated Health and Policy Research (IHPR) and coordinate data analytics work to ensure accurate and timely communication and successful completion of research deliverables for contracts and grants.
Requirements
- Master’s degree and five years of experience in an area of research specialty;
- Strong proficiency in SAS, SQL, R, and Python;
- Experience/training in health services research;
- At least 6 years of experience with the analysis of claims/encounter data;
- Strongly prefer an understanding of Medicaid, Medicare, and/or private healthcare claims data systems;
- Proficiency in SAS and SQL or other statistical analytical software programs (e.g., R, Python, Stata);
Responsibilities
- Works independently under the direction of the Principal Investigators to design pipelines; manages large databases of health insurance claims from Medicaid, Medicare, all-payer data warehouses, and other state administrative datasets;
- Engages in advanced data analytics to integrate separate datasets from multiple sources, including obtaining, validating, and compiling data to create summary files and dashboards for both internal and external use;
- Directs data management and analytic projects to develop complex, multi-dimensional products;
- Conceptualize and complete complex projects with thorough documentation and demonstration of applied logic;
- Trains and mentors staff to expand skill sets to address higher-level tasks to support research, automate processes to increase efficiency, and enhance product development;
Other
- Master’s degree in health, social sciences, or epidemiology;
- Ability to plan for and work on multiple projects concurrently;
- Ability to exercise sound judgment in making decisions and maintain thorough documentation of the decision-making process;
- Exemplary communication skills and ability to communicate effectively, both verbally and in writing, complicated processes to diverse audiences;
- Strong commitment to rigorous research methods, objectivity, and accuracy of findings, and reproducibility of results;
