Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Data Scientist London, England

Group M Worldwide Inc.
London
5 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist London, United Kingdom

Sr Data Scientist (London)

Associate (Data Scientist) - London, Wroclaw

Associate (Data Scientist) - London, Wroclaw

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

WHO WE ARE

Choreograph is WPP’s global data products and technology company. We’re on a mission to transform marketing by building the fastest, most connected data platform that bridges marketing strategy to scaled activation.

We work with agencies and clients to transform the value of data by bringing together technology, data and analytics capabilities. We deliver this through the Open Media Studio, an AI-enabled media and data platform for the next era of advertising.

We’re endlessly curious. Our team of thinkers, builders, creators and problem solvers is over 1,000 strong, across 20 markets around the world.

WHO WE ARE LOOKING FOR

We are looking for a Senior Data Scientist who has experience and expertise in a wide range of methodologies, toolkits and applications to a variety of problems in the media landscape.

As a Senior Product Data Scientist, you will collaborate with teams from Engineering, Product, and fellow data scientists to develop advanced models and solutions. Your responsibilities will include conducting hypothesis testing, applying statistical analysis techniques, and designing and implementing modeling methodologies. You will engage with stakeholders to understand their requirements, provide regular updates on project progress, and translate complex technical concepts into actionable insights for both technical and non-technical audiences.

You will be a part of a vibrant group, collaborating with specialist and business teams, demonstrating your technical knowledge, growing your soft/interpersonal skills and helping develop and improve the product offerings of Choreograph.

WHAT YOU’LL DO

  • Rapidly prototype as part of a product team, and iterate on experimental projects using a hacker mentality to test hypotheses, validate assumptions, and drive innovation.
  • Align experiments to answer business and product-centered questions, ensuring a clear understanding of the objectives and desired outcomes.
  • Understand business analysis techniques, including SWOT (Strengths, Weaknesses, Opportunities, Threats) and SOAR (Strengths, Opportunities, Aspirations, Results) analysis to understand business priorities and align data science initiatives with organizational objectives.
  • Collaborate with data engineers, product teams, and stakeholders to develop and create data products that address specific business needs and requirements with minimal guidance.
  • Support and upskill more junior team members.
  • Gather, analyze, and visualize data to create compelling and informative narratives for stakeholders, using storytelling techniques to effectively communicate insights and recommendations.
  • Stay up to date with the latest advancements, trends, and research in AI, data science, machine learning, and related technologies.
  • Document experimental methodologies, findings, and insights to ensure transparency, reproducibility, and knowledge sharing within the team and across the organization.
  • Collaborate with cross-functional teams to define data requirements, design experiments, and develop strategies to extract meaningful insights from complex datasets.
  • Conduct rigorous data analysis, applying statistical techniques and data visualization to uncover patterns, trends, and actionable insights.
  • Evaluate and recommend appropriate tools, frameworks, and technologies to enhance experimentation, analysis, and data storytelling capabilities.
  • Adhere to data governance and privacy policies to ensure compliance with relevant regulations and industry best practices.

WHO YOU ARE

  • Experience analyzing large volumes of data.
  • Good understanding of data fusion, enrichment and synthetic methodologies.
  • Excellent analytical skills and strong statistical knowledge, as well as interest in applying them to complex problems.
  • Programming proficiency in Python.
  • Extensive experience solving analytical problems using quantitative approaches.
  • A passion for empirical research and for answering hard questions with data.
  • A flexible analytic approach that allows for results at varying levels of precision.
  • Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner.

If you are ready to be at the forefront of the AdTech industry, shaping its future, and driving success for both Choreograph and our clients, we encourage you to apply and join our team.

Choreograph is the beating heart of data inside WPP’s media investment group, GroupM, the world’s leading media investment company responsible for more than $60 billion in annual media investment. Discover more about Choreograph atwww.choreograph.com.

GroupM and all its affiliates embrace and celebrate diversity, inclusivity, and equal opportunity. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the more great work we can create together.

#LI-Promoted

#J-18808-Ljbffr

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.