Meta is seeking to solve the challenge of driving strategic insights, operational support, and data foundations across multiple domains that merge AI solutions (e.g., AI Agents, LLM-generated labels for model training and evals, LLM-based content moderation) and Human-provided solutions (e.g., Customer Support Agents, Human-generated labels for training and evals, and Human-driven content moderation). The goal is to evaluate model and human performance against incoming requirements, drive customer satisfaction, protect voice, reduce harm, retain millions of users and billions in revenue, and drive down operational costs.
Requirements
- BS degree in a quantitative discipline (e.g., statistics, operations research, econometrics, computer science, engineering), or BS/MS in a quantitative discipline with equivalent working experience
- A minimum of 7 years of work experience (3+ years with a Ph.D.) in applied quantitative field, including + years of experience managing analytics teams
- 7+ years of experience in a team leadership role, including 2+ years of experience with people management through layers
- Experience communicating both in low-level technical details as well as high-level strategies
- Experience in cross-functional partnership among teams of Engineering, Design, Product Management, Data Engineering
- Experience with driving product roadmap and execution
- Expertise in AI Agentic solutions, LLM performance and evals
Responsibilities
- Labeling spend management: Inform and drive multi-billion spend management and optimizations
- develop and execute a comprehensive data science strategy that aligns with the organization’s overall goals and objectives
- Labeling delivery performance: Inform and drive labeling performance improvements and optimizations in an evolving mix of AI-generated labels and Human-generated labels
- Customer support performance: Inform and drive customer support performance improvements and optimizations in an evolving mix of AI Agents and Human Agents
- develop and execute a comprehensive data science strategy for evolving the role of AI and human experts in providing industry leading customer support
- High Data Science Bar: Grow and manage a high-performing Data Science team that remains agile and impactful under a high degree of uncertainty during technological transformations
- Collaborate closely with Directors and VP level stakeholders in a highly-matrixed organization dynamics
Other
- BS degree in a quantitative discipline (e.g., statistics, operations research, econometrics, computer science, engineering), or BS/MS in a quantitative discipline with equivalent working experience
- A minimum of 7 years of work experience (3+ years with a Ph.D.) in applied quantitative field, including + years of experience managing analytics teams
- 7+ years of experience in a team leadership role, including 2+ years of experience with people management through layers
- Communication skills in VP-level leadership forums
- Interest in an ecosystem role that will encompass a well-defined but broad set of initiatives (e.g., budget management, operational efficiency, and customer support performance)
