Quantitative Research Scientist, Demography & Surveys

Meta; New York (NY); On-site; USD 177,000 - 247,000; Full time

Job summary

Meta seeks a Research Scientist in Demography and Survey Sciences to own research end-to-end. You will navigate trade-offs while designing projects, proposing methodologies, analyzing data, and communicating results to broad audiences to drive decisions.

Qualified candidates will have 8+ years in quantitative research and expertise in measurement, causal inference, and AI-enabled methods, with strong Python/R and SQL skills and experience with large relational datasets.

Qualifications

• 8+ years of experience in quantitative research, survey methodology, or a related field.
• Advanced degree in economics, political science, sociology, psychology, or related quantitative field.
• Experience designing original research to address complex questions.
• Strong data manipulation and analysis skills in Python/R, SQL.

Responsibilities

• Shape the research agenda and drive projects end-to-end.
• Collaborate with product teams to define survey methodology questions and measurement.
• Apply quantitative methods to answer research questions and provide actionable insights.
• Develop novel approaches when traditional methods fall short.
• Provide teams with measurement strategies to support product and business decisions.
• Communicate analyses and results clearly to executives and other stakeholders.

Skills

Quantitative research

Survey methodology

Causal inference

Econometrics

Regression modeling

Data analysis

Python/R

SQL

Education

Bachelor's/Master's/Ph.D. in social sciences or quantitative field

Tools

Python

R

SQL

Job description

Meta seeks a Research Scientist in Demography and Survey Sciences to own research end-to-end. You will navigate trade-offs while designing projects, proposing methodologies, analyzing data, and communicating results to broad audiences to drive decisions.

Qualified candidates will have 8+ years in quantitative research and expertise in measurement, causal inference, and AI-enabled methods, with strong Python/R and SQL skills and experience with large relational datasets.