Data Scientist, Product Analytics

Meta is seeking a Staff Data Scientist to drive product strategy and decision-making across our family of applications, including Facebook, Instagram, Messenger, WhatsApp, and Meta's emerging platforms. In this role, you will operate as a company-level expert in product analytics, partnering with Product, Engineering, and cross-functional leadership to translate complex, large-scale behavioral data into actionable insights that shape the experiences of billions of people worldwide. You will lead the design of rigorous analytical frameworks, advance forecasting and predictive modeling capabilities, and influence the highest-priority product investments through data-driven storytelling and strategic recommendations.

Responsibilities

Lead the design and execution of complex analytical projects across product areas, applying advanced statistical methods, causal inference, and experimentation to evaluate product impact at scale Develop and maintain sophisticated predictive models and forecasting frameworks to inform product roadmaps, goal setting, and resource prioritization Define and evolve success metrics and measurement strategies for product initiatives, ensuring goals accurately reflect user and business value Identify and size high-impact product opportunities by synthesizing behavioral data, qualitative signals, and business context across multiple data sources Partner with Product and Engineering teams to design and analyze large-scale A/B tests and feature rollouts, translating results into clear recommendations for product direction Build scalable, self-service data pipelines and visualization interfaces that enable cross-functional teams to explore and act on product performance data independently Communicate complex analytical findings to diverse audiences including product leadership and executives through concise, compelling data narratives and presentations Contribute to functional data science strategy by proactively identifying methodological gaps, championing analytical best practices, and setting goals across teams Mentor other data scientists on analytical design, hypothesis formulation, and quantitative modeling, elevating the overall quality and rigor of the team's work Collaborate with Data Engineering and Research partners to improve data infrastructure, eliminate bias in data collection, and ensure analytical outputs accurately represent the populations of interest

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience A minimum of 6 years of work experience in analytics (a minimum of 4 years with a Ph.D.) Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent practical experience Experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), and/or statistical/mathematical software (e.g., R) Master's or Ph.D. Degree in a quantitative field Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Experience in 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 Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)