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 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 plansMeta builds technologies that help people connect, find communities, and grow businesses. 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).