National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Data Science Manager, Verification & Premium Support

Meta
London
1 month ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Senior Data Scientist - B2B

Senior Data Scientist (Fraud) | London, UK

Senior Data Scientist (Fraud)

Data Science & Analytics Team Lead

Data Science & Analytics Team Lead

Data Science Manager, Verification & Premium Support

As a Data Science Manager at Meta, you will help shape the future of the experiences we build for billions of people and hundreds of millions of businesses, creators, and partners around the world. You will apply your people leadership, project management, analytical, and technical skills, creativity, and product intuition to one of the largest data sets in the world. You will collaborate on a wide array of product and business problems with a diverse set of cross-functional partners across Product, Engineering, Research, Data Engineering, Operations, Sales, Finance, and others. You will influence product strategy and investment decisions with data, be focused on impact, and lead and grow a productive and impact-oriented team. By joining Meta, you will become part of a diverse analytics community dedicated to skill development and career growth in analytics and beyond.

About the role:

  1. Product leadership:You will use data to understand the product and business ecosystem, quantify new opportunities, identify upcoming challenges, and shape product development to bring value to people, businesses, and Meta. You will help develop strategy and support leadership in prioritizing what to build and setting goals for execution.
  2. Analytics:You will guide product teams using data and insights. You will focus on developing hypotheses and employ a diverse toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.
  3. Communication and influence:You won’t simply present data, but tell data-driven stories. You will convince and influence leaders using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted thought partner.
  4. People leadership:You will inspire, lead and grow a team of data scientists and data science leaders.

Responsibilities

  1. Drive analytics projects end-to-end in partnership with teams from Engineering, Product Management and across the Analytics community to inform, influence, support, and execute product strategy and investment decisions.
  2. Inspire, lead, and grow a team of data scientists and manager(s) to fulfill our longer-term vision.
  3. Actively influence the design of the strategy and shaping of the roadmap within this scope. Generate and use team insights to set and prioritize longer-term goals.
  4. Develop understanding of complex distributed systems and sub-components, as well as broader industry challenges, to identify present and future risks and opportunities.
  5. Work with large and complex data sets to solve a wide array of complex problems using different analytical and statistical approaches.
  6. Grow analytics skills around you, upskilling your team, engineers, and others, to increase overall team impact.

Minimum Qualifications

  1. 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.
  2. A minimum of 7 years of work experience (3+ years with a PhD) in an applied quantitative field, including 2+ years of experience managing analytics teams.
  3. 5+ years of experience in a team leadership role, including 2+ years of experience with people management through layers.
  4. Experience communicating both in low-level technical details as well as high-level strategies.
  5. Experience in cross-functional partnership among teams of Engineering, Design, Product Management, Data Engineering.
  6. Experience with driving product roadmap and execution.

Preferred Qualifications

  1. Master’s or Ph.D. degree in Mathematics, Statistics, Computer Science, Engineering, Economics, or another quantitative field.
  2. Proven track record of leading analytics teams that deliver on multiple projects or programs across regions or business groups.
  3. 7+ years of experience doing quantitative analysis, statistical modeling or machine learning in the experimentation space.
  4. A minimum of 2 years of experience working on consumer-facing products.

About Meta

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.

#J-18808-Ljbffr

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Present AI Models to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

In today’s competitive job market, AI professionals are expected to do more than just build brilliant algorithms—they must also explain them clearly to stakeholders who may have no technical background. Whether you're applying for a role as a machine learning engineer, data scientist, or AI consultant, your ability to articulate complex models in simple terms is fast becoming one of the most valued soft skills in interviews and on the job. This guide will help you master the art of public speaking for AI roles, offering tips on structuring presentations, designing effective slides, and using storytelling to make your work resonate with any audience.

AI Jobs UK 2025: 50 Companies Hiring Now

Bookmark this guide – we refresh it every quarter so you always know who’s really scaling their artificial‑intelligence teams. Artificial intelligence hiring has roared back in 2025. The UK’s boosted National AI Strategy funding, record‑breaking private investment (£18.1 billion so far) & a fresh wave of generative‑AI product launches mean employers are jockeying for data scientists, ML engineers, MLOps specialists, AI product managers, prompt engineers & applied researchers. Below are 50 organisations that have advertised UK‑based AI vacancies in the past eight weeks or formally announced growth plans. They’re grouped into five easy‑scan categories so you can jump straight to the kind of employer – & culture – that suits you. For each company you’ll find: Main UK hub Example live or recent vacancy Why it’s worth a look (tech stack, culture, mission) Use the internal links to browse current vacancies on ArtificialIntelligenceJobs.co.uk – or set up a free job alert so fresh roles land in your inbox.

Return-to-Work Pathways: Relaunch Your AI Career with Returnships, Flexible & Hybrid Roles

Stepping back into the workplace after a career break can feel like embarking on a whole new journey—especially in a cutting-edge field such as artificial intelligence (AI). For parents and carers, the challenge isn’t just refreshing your technical know-how but also securing a role that respects your family commitments. Fortunately, the UK’s tech sector now boasts a wealth of return-to-work programmes—from formal returnships to flexible and hybrid opportunities. These pathways are designed to bridge the gap, equipping you with refreshed skills, confidence and a supportive network. In this comprehensive guide, you’ll discover how to: Understand the booming demand for AI talent in the UK Leverage transferable skills honed during your break Overcome common re-entry challenges Build your AI skillset with targeted training Tap into returnship and re-entry programmes Find flexible, hybrid and full-time AI roles that suit your lifestyle Balance professional growth with caring responsibilities Master applications, interviews and networking Whether you’re returning after maternity leave, eldercare duties or another life chapter, this article will equip you with practical steps, resources and insider tips.