Data Scientist, Product Analytics

Summary

Meta builds technologies that help people connect, find communities, and grow businesses. The Data Scientist, Product Analytics will use quantitative analysis, experimentation, data mining, and product insights to guide product strategy, measure success, identify opportunities, and influence investment decisions across Meta’s products. The role partners with Product, Engineering, and other cross-functional teams to develop data-driven recommendations and roadmaps.

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

Skills

• - Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• - Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent
• - 4+ years of work experience in analytics, data querying languages such as SQL, scripting languages such as Python, and/or statistical mathematical software such as R (minimum of 2 years with a Ph.D.)
• - 4+ years of experience solving analytical problems using quantitative approaches, understanding ecosystems, user behaviors & long-term product trends, and leading data-driven projects from definition to execution [including defining metrics, experiment, design, communicating actionable insights]
• - Master's or Ph.D. Degree in a quantitative field
• - 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

Qualifications

Must Haves

• - Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• - Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent
• - 4+ years of work experience in analytics, data querying languages such as SQL, scripting languages such as Python, and/or statistical mathematical software such as R (minimum of 2 years with a Ph.D.)
• - 4+ years of experience solving analytical problems using quantitative approaches, understanding ecosystems, user behaviors & long-term product trends, and leading data-driven projects from definition to execution [including defining metrics, experiment, design, communicating actionable insights]

Nice to Haves

• - Master's or Ph.D. Degree in a quantitative field
• - 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

Benefits

• Dedicated to skill development and career growth in analytics and beyond