The Central Product Equity Team's vision is for a world where technology advances equity globally, and people of all backgrounds feel safe, uplifted, and empowered through Meta's products. We seek to elevate the quality of Meta's products and create experiences that can bring equal value to communities facing systemic oppression. This Academic Collaborator will support the Central Product Equity team's goal to raise the bar for innovation cross-industry and set industry standards for equitable product development through the creation of novel methodologies and approaches.We are seeking a quantitative researcher to support the development of scaled equity measurement and benchmarking for Meta products. This fixed-term position will help us establish relevant measurement and benchmarking for Meta's suite of products as well as evaluate progress towards our goals, including making existing products more equitable. Research and collaboration is expected to last for 6-12 months but may change based on business needs.

• Develop methodology to assess online and offline equity impact of products
• Work closely with teams to identify research topics
• Conduct research using a variety of quantitative methods
• Design studies that explore unmet needs as well as current behavior and attitudes
• Generate insights to fuel ideation, evaluate designs and guide product roadmaps
• Work cross-functionally with product management, analytics, content design, product design, engineering, and marketing to communicate results to various audiences and integrate measurement strategy into various functions' work streams
• Externalize internal research and product development processes and approaches related to Equitable product development

• MS/PhD in the social sciences
• Demonstrated experience in quantitative research methodologies (e.g., survey sampling and design, regression modeling, experimental design, behavioral data analysis, causal inference with observable data, causal impact evaluation)
• Experience using SQL/Hive, Python, and/or R to analyze large datasets (> 1TB)
• Familiarity with machine learning, specifically content classification methods
• In-depth understanding in assessing structural and systemic biases in science and technology, and a demonstrated experience in understanding of identity considerations as they relate to measurement.
• Evidence of interest in exploring the impact of new technologies and offline societal systems.

• Experience establishing and applying offline equity measurement, including experience measuring real-world impact of equity efforts (within or outside of the technology space).
• Experience identifying and working with vendors on end-to-end research design and execution
• While the disciplinary specialization for this position is open, we are particularly interested in candidates with backgrounds in assessing societal inequities and whose research and practice transcends disciplinary boundaries, including but not limited to: algorithmic inequality, critical algorithm or data studies, decolonization and postcolonial studies, ethics and politics of computing, ethnic studies, history, political science, science and technology studies, sociology, racial capitalism and platform studies, information technologies, or other related fields.