Research Scientist, Demography and Survey Sciences
Immigration summary
Visa sponsorship
This employer sponsors this kind of work repeatedly, and is still filing this year.
5,686 recent H-1B filings · 572 similar-role filings
View visa evidenceGreen card sponsorship
This employer has recently sponsored green cards at scale.
742 recent certified PERM filings · 107 similar-role filings
View green card evidenceJob description
The Demography and Survey Science team's mission is to improve the way we make decisions and measure impact both within and outside of Meta. We collect and analyze rich survey and behavioral datasets to understand new challenges, solve problems, and shape decisions. We are looking for quantitative social scientists with experience answering complex research questions to join us in this effort. Our interdisciplinary team includes those with expertise in statistical inference, survey methodology, causal inference and econometrics, regression modeling, exploratory data analysis, and mathematical demography, among other areas. In this role, you'll own research end-to-end. This means you'll navigate trade-offs while designing projects, proposing appropriate methodologies, analyzing data, and communicating results to broad audiences in order to drive impactful decisions. Qualified candidates may include social scientists, applied statisticians, or other applied researchers with expertise in quantitative research methods, experience working with large datasets and relational databases, and experience with survey methodology (e.g., bias correction, sampling). We are looking for candidates who can demonstrate methodological rigor, demonstrated communication skills, and experience making research design choices that balance competing tradeoffs effectively.
Responsibilities
- Help shape the research agenda and drive research projects from end-to-end
- Collaborate with product teams to define relevant questions about survey methodology and quantitative measurement
- Deploy appropriate quantitative methodologies to answer those questions
- Develop novel approaches where traditional methods won’t do
- Provide teams with usable measurement strategies and methodologies to meet their product and business decision needs
- Deliver insights and recommendations clearly to relevant audiences
Minimum Qualifications
- 8+ years of experience in quantitative research, survey methodology, or a related field
- Bachelor's, Master's or Ph.D. in the social sciences (e.g., Economics, Political Science, Sociology, Psychology, Communication), or in a quantitative field (e.g., Statistics, Informatics, Econometrics)
- Demonstrated experience in designing original research to address complex questions
- Demonstrated expertise in data manipulation and analysis software and programming languages (Python/R, SQL)
- Expertise and applied experience in measurement (e.g., survey design and analysis, experiment design, bias correction, measurement models, data collection, log data) and statistical inference (e.g., causal, Bayesian, machine learning)
- Experience initiating and driving research projects to completion with minimal guidance
- Experience communicating analyses and results to any audience, including executives
- Demonstrated experience in distilling and communicating research insights to influence the thinking, decision-making, and actions of diverse audiences
Preferred Qualifications
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Experience with qualitative methods such as focus groups, in-depth interviewing, cognitive testing
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
- Experience working with executive or leadership-level stakeholders
- Experience working with online survey panel vendors (e.g., YouGov, Ipsos, Kantar, SSRS)
- Experience translating often abstract stakeholder requests into actionable research plans
Sponsorship evidence
Why Openbound reached the conclusions above.
Visa sponsorship evidence
Current posting
Silent on sponsorship
Employer H-1B history
- 5,686
- recent certified H-1B filings
- 3,007
- new-hire petitions
- 572
- filings for similar roles
- 5,150
- so far in FY2026
Filed titles like this role: research scientist · ai research scientist · ux research scientist · al research scientist
More evidence details
- 572 certified H-1B filings for this same role, 3,007 new-hire petitions across the employer, and 2,752 new hires already this year
- 572 certified H-1B filings for this same role
- 5,686 recent certified H-1B filings across the employer
- Still filing this year — 5,150 filings in FY2026
- 2,778 USCIS H-1B new-employment approvals, counted separately from LCA filings
- Strong filing activity in CA
- 11,582 further USCIS approvals for extensions or transfers
- The posting says nothing about sponsorship either way
Strong filing activity in CA.
Green card sponsorship evidence
Employer PERM history
- 742
- recent certified PERM filings
- 107
- filings for similar roles
- 478
- filings in this location
Filing history reflects past employer behavior; it isn't a promise for this opening.
All open roles at MetaHow Openbound evaluates sponsorship
Visa history uses official U.S. Department of Labor H-1B LCA disclosure data and USCIS H-1B petition history. Green card history uses DOL PERM disclosure data. Each is read for the employer as a whole, for roles like this one, and for this location, weighted toward the most recent fiscal years.
An employer is matched to its filing entities by verified legal name and reviewed aliases; a match is never made on a name resemblance alone. Where no verified entity can be matched, the page says so and draws no conclusion from the absence. 1,277 filing titles were examined for this employer.
What this posting states outranks history in both directions, and an employer's published policy outranks past filings. Filing history reflects past behavior; it is not a promise of sponsorship for this opening, and none of this is legal advice.