Data Scientist, PSI: Innovation & Impact (Remote)

American Institutes for Research; United States; Hybrid; USD 114,000 - 140,000; Full time

Job summary

American Institutes for Research seeks a Data Scientist to join the Project Success and Innovation (PSI) team and the Employment and Economic Opportunity Program (EEOP). You will lead end-to-end quantitative workflows, build scalable analytic tools, and translate findings for clients and stakeholders.

The role emphasizes causal and non-causal analyses, ML methods, and developing reproducible pipelines, with opportunities to work remotely within the United States or from AIR offices.

Qualifications

• Master's or doctoral degree in a quantitative field with coursework or experience in causal inference and statistical modeling.
• Experience with complex survey data, large datasets, and education/health/social policy questions.
• Experience with machine learning/AI methods, including large language models in research.
• Interest in building tools used by others and ability to support colleagues.

Responsibilities

• Build and maintain analytic tools, code libraries, and pipelines for AIR research teams.
• Lead quantitative analyses, including causal/non-causal questions, and document reproducible workflows.
• Review and improve code quality from junior staff and support reproducible practices.
• Draft analytic content for client reports and translations for non-technical audiences.
• Track deliverables and contribute to proposals.

Skills

R/Python

Stata

Git

Quarto

R Markdown

Jupyter

Communication

Reproducible research

Education

Master's or doctoral degree in a quantitative field

Tools

R

Python

Stata

Git

Quarto

R Markdown

Jupyter

Job description

American Institutes for Research seeks a Data Scientist to join the Project Success and Innovation (PSI) team and the Employment and Economic Opportunity Program (EEOP). You will lead end-to-end quantitative workflows, build scalable analytic tools, and translate findings for clients and stakeholders.

The role emphasizes causal and non-causal analyses, ML methods, and developing reproducible pipelines, with opportunities to work remotely within the United States or from AIR offices.