Data Scientist (Technical Leadership)

Meta seeks an experienced Data Scientist (Technical Leadership) in Los Angeles to lead analytics efforts, shape product direction with data, and drive measurable outcomes across product and technical initiatives.

Responsibilities

• Analyze large, complex datasets to tackle a range of challenging product and technical problems using varied analytical and statistical methods
• Use quantitative analysis, experimentation, and data mining to develop product strategies for audiences that include billions of people and hundreds of millions of businesses
• Define and track success for product efforts through goal setting, forecasting, and monitoring key product metrics to detect trends
• Identify opportunities to more responsibly leverage cutting edge technology
• Define, evaluate, and test levers to improve product performance, then influence roadmaps using insights and recommendations
• Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions
• Operate effectively in ambiguity by forming clear hypotheses, using data-driven decisions, and proactively flagging areas needing deeper investigation

Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience
• 8+ years of experience in data science or analytics, including leading analytics work in an IC capacity and collaborating with Engineering and cross-functional partners to guide data-informed product planning, prioritization, and strategy development
• Experience working with multiple stakeholders and cross-functional teams, including Engineering, PM/TPM, Analytics, and Finance
• Strong framing and communication skills

Benefits

• $210,000/year to $281,000/year + bonus + equity + benefits

Preferred Qualifications

• Ability to integrate AI tools to optimize or redesign workflows with measurable impact (for example, efficiency gains or quality improvements)
• Master’s or Ph.D. in a quantitative field
• Evidence of ongoing AI skill development (for example, prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience with predictive modeling, machine learning, and experimentation or causal inference methods
• Experience implementing responsible, ethical AI practices, including risk assessment, bias mitigation, and quality and accuracy reviews

Location: Los Angeles, CA (onsite)

Experience: 8+ years