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About the Role

Meta is seeking a Research Scientist to join the Quantitative Growth Research team. This role involves applying rigorous quantitative methods to understand user behavior, product adoption, and growth dynamics across Meta's products. You will design and execute large-scale studies, develop causal inference frameworks, and translate complex behavioral data into actionable insights to shape product strategy and drive sustainable growth. You will partner closely with product, engineering, and data science teams to define research agendas that influence how billions of people discover and engage with Meta's products.

Responsibilities

Design and execute quantitative research studies, including surveys, behavioral data analyses, and observational studies, to understand user acquisition, retention, and engagement patterns.
Develop and apply causal inference methods to evaluate the impact of product changes on growth outcomes.
Build and validate measurement frameworks connecting user behavior signals to long-term growth and retention metrics.
Collaborate with product managers, engineers, and data scientists to translate research findings into product strategy and roadmap decisions.
Identify gaps in existing measurement approaches and design novel methodologies to address them.
Communicate complex quantitative findings to technical and non-technical stakeholders through written reports, presentations, and data visualizations.
Contribute to team-level research goals by identifying high-priority growth questions and scoping research projects.
Leverage AI-integrated workflows and analytical tools to accelerate research design, data processing, and insight generation.
Advise cross-functional partners on appropriate research methods, statistical interpretation, and the limitations of quantitative findings.

Requirements

PhD in a quantitative field such as economics, statistics, psychology, computational social science, or a related discipline.
Experience conducting quantitative research using methods such as experimentation, causal inference, survey research, or large-scale behavioral data analysis.
Experience applying statistical modeling techniques 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 and staying current with emerging AI technologies.
Experience adhering to and implementing responsible, ethical AI practices.
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact.
Track record of publishing or presenting quantitative research findings in peer-reviewed venues or applied research settings.

Skills

Causal inference
Survey research
Behavioral data analysis
Statistical modeling
Regression
Survival analysis
Bayesian methods
Python
R
SQL
Prompt engineering
Agent orchestration
Risk assessment
Bias mitigation
Quality and accuracy reviews

Education Level

PhD in a quantitative field such as economics, statistics, psychology, computational social science, or a related discipline

Salary/Compensations

$147,000/year to $208,000/year

Benefits

bonus
equity
benefits