Data Scientist, Product

Meta is seeking a Data Scientist to operate at the forefront of product intelligence, shaping how billions of people experience Meta's family of apps and platforms. In this role, you will serve as a company-level expert in product data science, partnering with product, engineering, and business leaders to define strategy, uncover high-impact opportunities, and drive decisions that influence the direction of Meta's core products. You will pioneer analytical frameworks, experimental designs, growth strategies, and establish best practices that elevate data science across the organization. Responsibilities • Define and drive the analytical strategy for complex, ambiguous product areas, translating business questions into rigorous research designs and measurable hypotheses • Develop and own advanced predictive and causal models that generate actionable product insights at scale, serving as an industry-level expert in model design and evaluation • Establish and champion organization-wide standards for data preparation, visualization, and self-service analytics interfaces that enable cross-functional decision-making • Synthesize outputs from statistical models, experimentation frameworks, and qualitative analyses into clear, data-driven narratives tailored to executive and cross-functional stakeholders • Identify and size strategic product opportunities by evaluating business impact, prioritizing across competing initiatives, and aligning analytical investments with long-term product goals • Collaborate with product, engineering, design, and operations partners to co-develop success metrics, monitor operational performance, and track trends that inform future-focused product strategy • Pioneer novel applications of forecasting, machine learning, and experimentation methodologies to solve previously intractable product problems and drive organization-wide adoption • Build and maintain production-quality data pipelines and analytical codebases, ensuring reliability, efficiency, data privacy compliance, and scalability • Serve as a recognized internal thought leader and trusted advisor across multiple product and business areas, influencing key leaders and shaping functional data science strategy • Mentor other data scientists and cross-functional partners by sharing analytical frameworks, reviewing methodologies, and developing shared tools and resources that raise the overall quality of data science practice Minimum Qualifications • 12+ years of experience in data science, applied statistics, or a related quantitative field within a product or technology organization • Experience designing and executing end-to-end research plans including hypothesis formulation, data collection strategy, statistical modeling, and stakeholder communication for large-scale product decisions • Experience developing and evaluating predictive models, causal inference frameworks, and experimentation methodologies (such as A/B testing and quasi-experimental designs) at production scale • Experience writing and maintaining production-quality code in Python, SQL, or equivalent languages, including data pipeline development and statistical analysis • Experience influencing product or business strategy through data-driven narratives delivered to executive and cross-functional audiences Preferred Qualifications • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) • 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 establishing data science standards, reusable frameworks, or self-service analytics platforms adopted broadly across an organization or business domain • Experience applying machine learning or advanced forecasting methods to product growth, engagement, monetization, or user behavior problems at internet scale • Experience partnering with product and engineering leaders to define long-term roadmaps and translate ambiguous strategic questions into structured analytical programs • Experience in causal inference techniques such as difference-in-differences, instrumental variables, or synthetic control methods applied to observational product data Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.