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Mathematica applies expertise at the intersection of data, methods, policy, and practice to improve well-being around the world. We collaborate closely with public- and private-sector partners to translate big questions into deep insights that improve programs, refine strategies, and enhance understanding. Our work yields actionable information to guide decisions in wide-ranging policy areas, from health, education, early childhood, and family support to nutrition, employment, disability, and international development. Mathematica offers our employees competitive salaries, and a comprehensive benefits package, as well as the advantages of being 100 percent employee owned. As an employee stock owner, you will experience financial benefits of ESOP holdings that have increased in tandem with the company's growth and financial strength. You will also be part of an independent, employee-owned firm that is able to define and further our mission, enhance our quality and accountability, and steadily grow our financial strength. Learn more about our benefits here: https://www.mathematica.org/career-opportunities/benefits-at-a-glance

At Mathematica, we take pride in our commitment to diversity. Building an inclusive culture that draws on the individual strengths of employees from different ethnic backgrounds, cultures, lifestyles, abilities, and experience is key to our success.

We are seeking an intellectually curious Data Analytics Developer in any of our locations who is passionate about using big data to answer research questions that influence decision making in U.S. health care policy. The ideal candidate will work in languages such as Python and SQL. Individuals with an interest in confronting the challenges of working with large, complex data sets, an interest in data manipulation and analysis, and a desire to become a subject matter expert in health care data are strongly encouraged to apply.

Responsibilities:

• Working with large secondary data sources such as Medicare and Medicaid administrative claims data and survey data to effectively answer research questions about health care policy
• Providing creating and best practice solutions for data processing optimization, commonly on cloud computing platforms
• Ensuring data quality through all stages of data processing with rigorous quality control
• Iteratively informing requirements and specifications, which will include articulating findings and working with researchers to adjust specifications and code as interim results are found