Research Scientist, Quantitative Growth Research

Meta is seeking a Research Scientist to join the Quantitative Growth Research team, where you will apply rigorous quantitative methods to understand user behavior, product adoption, and growth dynamics across Meta's family of apps and services. In this role, you will design and execute large-scale studies, develop causal inference frameworks, and translate complex behavioral data into actionable insights that shape product strategy and drive sustainable growth.

You will partner closely with product, engineering, and data science teams to define research agendas that directly influence how billions of people discover and engage with Meta's products.

• Experience conducting quantitative research using methods such as experimentation, causal inference, survey research, or large-scale behavioral data analysis
• Experience applying statistical modeling techniques (e.g., regression, survival analysis, Bayesian methods, causal inference) to real-world product or growth research questions
• Experience translating quantitative research findings into product or business recommendations for cross-functional stakeholders
• Experience working with large-scale datasets using programming languages such as Python, R, or SQL
• Experience scoping and delivering independent research projects from problem definition through insight communication
• Familiarity with survey methodology, including questionnaire design, sampling strategies, and measurement validity in the context of user research
• Experience designing and analyzing large-scale experiments (A/B tests or quasi-experiments) in a consumer technology or growth context
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Track record of publishing or presenting quantitative research findings in peer-reviewed venues or applied research settings