Meta’s Products & Applied Research (PAR) team is where product-focused research meets real-world impact, taking breakthrough AI research and transforming it into products that reach billions. As part of Meta Superintelligence Labs (MSL), we’re driving the transformation of Meta’s core experiences—across Facebook, Instagram, WhatsApp, Threads, and beyond—by applying cutting-edge research to real-world products at massive scale. We are looking for a Data Scientist to join our PAR organization where you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world, by applying your technical skills, analytical mindset, and product intuition. In this role, you will collaborate on a wide array of product and business problems with a wide-range of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will use data and analysis to identify and solve product development's biggest challenges. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining Meta, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond. Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and Meta. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem. Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them. Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
Responsibilities
Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions
Qualifications
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 5+ years of experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, SAS, Matlab) 8+ years of work experience leading analytics work in IC capacity, working collaboratively with Engineering and cross-functional partners, and guiding data-influenced product planning, prioritization and strategy development Experience working effectively with and leading complex analytics projects across multiple stakeholders and cross-functional teams, including Engineering, PM/TPM, Analytics and Finance Experience with predictive modeling, machine learning, and experimentation/causal inference methods Experience communicating complex technical topics in a clear, precise, and actionable manner 10+ years of experience communicating the results of analyses to leadership teams to influence the strategy 10+ years of experience doing complex quantitative analysis in product analytics Master's or Ph.D. Degree in a quantitative field Bachelor's Degree in an analytical or scientific field (e.g. Computer Science, Engineering, Mathematics, Statistics, Operations Research) 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