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Meta

Data Scientist, Product Analytics

Meta · Data & Analytics, Data Science

London

Mid-level Still listed after 2 months

AI / MLPythonSQL

Last seen 2h ago

Posted
2mo ago

Posted on 9 September 2026

Workplace
Not specified

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Salary
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Salary range not shared by the company

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Visa sponsorship details unknown

Listing history First seen 60+ days ago
  • First seen 60+ days ago. We first saw this listing on 9 Sept 2026. That is when we found it, not necessarily when it was posted.

First seen 9 Sept 2026. Last checked 11 Nov, 23:17 UTC. We read each employer's own career page on a cycle and record what changes; this is what we observed, not a verdict on the role.

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As a Data Scientist at Meta, you will shape the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Oculus). By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a varied set 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 an 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

Minimum Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

A minimum of 6 years of work experience in analytics (minimum of 4 years with a Ph.D.)

Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent practical experience

Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R)

Preferred Qualifications

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

About Meta

Meta concentrates its European engineering in Dublin, London and Paris, working on infrastructure, AI and core product. Headcount has been volatile since 2022, so treat the size of the board as a snapshot rather than a trend.

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