Meta is seeking a Data Scientist to partner with product teams and drive data-informed decision making across Meta's family of apps and platforms. In this role, you will apply rigorous quantitative and qualitative analysis to understand user behavior, measure product impact, and shape the direction of product strategy. You will design and analyze experiments, build predictive models, and develop scalable data pipelines and dashboards that empower cross-functional teams to act on insights. Your work will directly influence product roadmaps and help Meta build experiences that serve billions of people worldwide.
Responsibilities
- Design and evaluate A/B experiments to measure the causal impact of product changes on user behavior and key product metrics
- Develop and maintain predictive models and statistical frameworks to generate actionable insights that inform product strategy
- Build scalable data pipelines and self-service visualization interfaces that enable cross-functional partners to explore and interpret product performance data
- Define success metrics and measurement frameworks that connect product goals to business outcomes
- Conduct exploratory and confirmatory analyses on large-scale behavioral datasets to identify opportunities and surface risks
- Collaborate with product managers, engineers, and designers to translate analytical findings into prioritized product decisions
- Communicate complex analytical results clearly to technical and non-technical stakeholders through written narratives and data presentations
- Advise cross-functional partners on analytical design, hypothesis formulation, and interpretation of quantitative and qualitative research
- Integrate AI tools into analytical workflows to accelerate insight generation, improve reproducibility, and expand the scope of analyses
- Contribute to team-level goal setting by sizing opportunities, tracking operational performance, and identifying gaps in existing measurement approaches
Minimum Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- Experience in data science, applied analytics, or a related quantitative field working on consumer or enterprise products
- Experience designing and analyzing controlled experiments, including hypothesis formulation, statistical testing, and interpretation of results
- Experience writing production-quality code in SQL and at least one scripting language such as Python or R to manipulate and analyze large-scale datasets
- Experience building predictive models using statistical or machine learning techniques and translating model outputs into product recommendations
- Experience developing data visualizations and self-service dashboards to communicate product performance to diverse stakeholders Experience building forecasting models using time series methods to project product or business metrics
- 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 on social platforms, feed ranking, notifications, or engagement products where behavioral data is high-volume and high-dimensional
- Experience applying causal inference methods such as difference-in-differences, instrumental variables, or regression discontinuity in a product analytics context
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Demonstrated ability to influence product roadmap decisions through data storytelling and stakeholder alignment at the team or organizational level