Senior Systems Programmer, Healthcare Innovations

American Institutes for Research•Chicago, IL

1d•$140,000 - $160,000•Remote

About The Position

Join AIR as a Senior Systems Programmer and use your experience and expertise to help us deliver on our mission: to generate and use rigorous evidence that contributes to a better, more equitable world for all. This position will help drive innovation in data science, architect scalable programming solutions, and influence strategic decisions across AIR’s health portfolio. The Senior Systems Programmer will report to AIR's Healthcare Innovations Team, which supports high-quality implementation and produces rigorous evidence on the effectiveness of new approaches to care and payment—translating findings into actionable insights for policymakers, payers, providers, and patients. This position has the flexibility to work remotely within the United States (U.S.) or from one of AIR’s U.S. office locations . This does not include U.S. territories. About AIR: Founded in 1946 and headquartered in Arlington, Virginia, the American Institutes for Research (AIR) is a nonpartisan, not-for-profit organization that conducts behavioral and social science research and delivers technical assistance to address some of the most pressing challenges in the United States and globally. We generate evidence and apply data-driven solutions that expand opportunities and improve lives for all.

Requirements

Bachelor’s degree in Statistics, Data Science, Public Health, Economics, Epidemiology, or a related quantitative field; Master’s degree preferred.
Minimum of 8 years of hands-on experience in SAS programming, including experience with large-scale administrative or healthcare datasets.
Demonstrated leadership in managing programming teams and delivering high-impact analytic products.
Experience working in secure or virtual research environments and familiarity with data governance best practices.
Expert-level proficiency in SAS, including macro programming, data step processing, and statistical procedures.
Strong analytical and problem-solving skills with a focus on accuracy and efficiency.
Excellent organizational and time management skills with the ability to manage multiple priorities.
Effective communication skills with the ability to explain technical concepts to non-technical audiences.
Proven ability to work independently and collaboratively in a fast-paced, virtual team environment.
Applicants must be currently authorized to work in the U.S. on a full-time basis.
Depending on project work, qualified candidates may need to meet certain residency requirements.

Nice To Haves

Master’s degree preferred.
Experience with other statistical or data science tools (e.g., R, Python, SQL) is preferred, but not required.

Responsibilities

Lead and support the design, development, and implementation of advanced programming solutions for large-scale health research and evaluation projects.
Oversee data management workflows, including data extraction, transformation, validation, and integration from multiple sources (e.g., claims, EHR, survey data).
Develop and optimize reusable code libraries, macros, and templates to improve efficiency and consistency across projects.
Conduct complex statistical analyses and generate high-quality outputs including tables, listings, and visualizations for technical reports and publications.
Provide technical leadership and mentorship to programming teams, including code reviews, training, and guidance on best practices.
Collaborate with statisticians, researchers, and data scientists to translate analytical requirements into executable code.
Ensure compliance with data security protocols and regulatory requirements in secure computing environments.
Contribute to proposal development by designing analytic approaches, estimating level of effort, and drafting technical sections.
Identify and implement process improvements to enhance data quality, reproducibility, and workflow automation.
Represent AIR in client meetings and technical discussions, communicating complex programming concepts clearly and effectively.