Data Scientist Associate

American Institutes for Research•Chicago, IL

1d•$45 - $60•Remote

About The Position

AIR’s Technology Office is seeking a Data Science Associate to join a forward-thinking, innovative team of data scientists and software engineers. The team partners with clients to deliver data-driven solutions across web, mobile, analytics, and data management platforms, supporting data collection, communication, learning, and user experience initiatives. Data scientists at AIR apply a blend of technical expertise and theoretical knowledge to support cutting-edge research design, implementation, and capacity-building efforts. AIR is committed to supporting career growth through interdisciplinary collaboration, training opportunities, and a strong community of practice. Team members contribute to meaningful projects across a range of domains, including education, public health, workforce development, science and innovation policy, criminal justice, and housing. Our work balances modern agile development practices with rigorous research design, remaining outcomes-focused and aligned with client missions and goals. This position sits within AIR’s Data Science and Advanced Analytics (DSAA) group, which leverages advanced analytical methods to address complex research and public policy questions and to support evidence-based decision-making on critical social challenges. Candidates hired for the position may work remotely within the United States (U.S.) or from one of our U.S. office locations . This does not include U.S. territories. Occasional travel will be required for meetings, training sessions, and conferences. About AIR: Established in 1946, with headquarters in Arlington, Virginia, AIR is a nonpartisan, not-for-profit institution that conducts behavioral and social science research and delivers technical assistance to solve some of the most urgent challenges in the U.S. and around the world. We generate evidence and appl y data-driven solutions that expand opportunities and improve lives for all.

Requirements

Bachelor’s degree in computer science-related fields (e.g., Data Science, Data Engineering, Computer Science) with at least 2 years of experience, or a Master’s degree in a similar discipline.
Python programming proficiency is a core requirement.
Solution-oriented mindset with the ability to apply creative problem-solving techniques.
Excellent communicator able to engage effectively across all organizational levels—including in virtual environments—and translate complex technical concepts into clear, plain language.
Collaborative team player, able to work effectively in cross-functional teams and contribute to shared goals in a virtual environment.
Flexible and adaptable, comfortable working in dynamic environments and adjusting to changing priorities.
Proficient with database technologies such as MySQL and MS SQL Server.
Experience with cloud platforms including AWS, GCP, and Azure; hands-on exposure to Azure OpenAI API is preferred, but not required.
Familiarity with generative AI tools and applications for practical use cases.

Nice To Haves

Knowledge of Python web frameworks (e.g., Django, Flask) is advantageous.
Understanding of statistical packages like R, SAS, or STATA is preferred, but not required.
Interest in exploring and developing innovative tools for data-driven applications.

Responsibilities

Design and build cloud applications and data pipelines using platform-as-a-service and open-source tools.
Develop interactive dashboards, visualizations, and reports leveraging open-source or business intelligence tools.
Collect, validate, analyze, and interpret data using standard practices, supporting both quantitative and qualitative analysis.
Perform computer modeling and forecasting using standard software packages.
Architect and deploy advanced artificial intelligence solutions, including natural language processing, computer vision, automatic speech recognition, and generative AI.
Write clean, replicable, and well-documented code in shared environments; review and optimize code for efficiency.
Ensure data accuracy and integrity by developing systems for validation and maintenance.
Collaborate independently and in teams on moderately complex assignments under indirect supervision.
Coordinate project support needs and respond to requests from senior management and clients.
Present findings and contribute to internal and external meetings, occasionally organizing content.
Stay current with emerging technologies and recommend innovative solutions to complex problems.
Leverage external resources to enhance project outcomes and deliverables.