Meta

Data Scientist, Analytics (Technical Leadership)

Meta London, England, United Kingdom

Software Development · 10,001+ employees

Yesterday
data-scientist Principal (10+ yrs) Full-time United Kingdom
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About the role

The role involves leading complex analytics projects to inform product strategy and collaborating with cross-functional teams to define success metrics. You will be responsible for developing long-term data strategies, building instrumentation, and communicating actionable insights to executive leadership.

What they look for

Data Science Product Analytics SQL Python R Statistical Analysis Predictive Modeling Machine Learning Experimentation Causal Inference Data Mining Quantitative Analysis Strategic Planning Stakeholder Management AI Ethics Prompt Engineering

Requirements

Candidates must have over 10 years of experience in product analytics and a strong background in quantitative analysis and statistical modeling. A bachelor's degree in a technical or scientific field is required, with a master's or Ph.D. preferred.

Full description

We are seeking experienced Data Scientists to join our team and drive impact across various product areas. As a Data Scientist, you will collaborate with cross-functional partners to identify and solve complex problems using data and analysis. Your role will involve shaping product development, quantifying new opportunities, and ensuring products bring value to users and the company. You will guide teams using data-driven insights, develop hypotheses, and employ rigorous analytical approaches to test them. You will tell data-driven stories, present clear insights, and build credibility with stakeholders. By joining our team, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.

Responsibilities

  • Work with complex data sets to solve problems using analytical and statistical approaches
  • Apply technical expertise in quantitative analysis, experimentation, and data mining to develop product strategies
  • Identify and measure success through goal setting, forecasting, and monitoring key metrics
  • Partner with cross-functional teams to inform and execute product strategy and investment decisions
  • Build long-term vision and strategy for programs and products
  • Collaborate with executives to define and develop data platforms and instrumentation
  • Effectively communicate insights and recommendations to stakeholders
  • Define success metrics, forecast changes, and set team goals
  • Support developing roadmaps and coordinating analytics efforts across teams

Minimum Qualifications

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • Mathematics, Statistics, Operations Research) 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 experience leading analytics work in an 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

Preferred Qualifications

  • 10+ years of experience communicating the results of analyses to leadership teams to influence the strategy
  • Masters 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)
  • 10+ years of experience doing complex quantitative analysis in product analytics
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

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