Major Responsibilities:

Query, clean, and analyze large datasets using SQL, Python, and Snowflake. Sources may include Lightcast data, government and third-party data, and client datasets.

Build and maintain data pipelines and create indices or composite measures for custom analyses.

Apply statistical and quantitative methods, such as benchmarking, correlation, and trend analysis, to answer client questions.

Adapt proven methods into repeatable workflows, trial new research approaches, and apply core labor market economics concepts.

Develop client-ready materials in Excel, PowerPoint, and Word, as well as visualizations and dashboards in Tableau or similar tools.

Present research to clients and internal teams, and communicate findings in ways that reflect what the data can support.

Use LLM tools to assist with coding, debugging, documentation, data tasks, dashboards, and draft deliverables; review and refine outputs for accuracy and quality.

Keep current with AI tools relevant to labor market research and share useful approaches with the team.

Education and Experience:

2–4 years of experience in quantitative research, data analysis, or data science.

Bachelor’s or master’s degree in Economics, Public Policy, Data Science, Statistics, or another quantitatively focused field.

Experience working with APIs to access, integrate, and analyze data.