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

Apply Now

VP Data Science

Acxiom UK
City of London
5 days ago
Create job alert

We are seeking a VP Data Science to lead our Data Science function within Planning Agent, our AI-powered advertising planning platform used daily by IPG agency teams. This role will shape the future of agentic AI in marketing technology, driving innovation in how planners interact with intelligent systems across optimization, allocation, and planning workflows.


While the product is moving towards agentic, our agents remain grounded in machine learning and complex mathematical models (e.g., econometrics, reach modelling). Success in this role depends on bridging the best of both worlds: machine learning models that provide structure and accuracy, and agentic systems that draw on unstructured inputs such as media briefs and contextual data. This combination allows planners to make decisions that are both reliable and informed by real-world context.


As the leader of our Data Science organization, you will oversee a team of 10+ senior data scientists distributed across Europe, guiding them in the design, implementation, and productizing of multi-agent workflows. While grounded in technical leadership, this role blends strategy and hands-on expertise: setting the data science roadmap, ensuring delivery at scale to build reliable, production-ready agents.


This is a leadership role with strong technical depth. You’ll serve as both a coach and an architect of the team, shaping best practices for data science in agentic systems, while partnering closely with Engineering and Product.


Tasks & Responsibilities


  • Lead and manage a distributed team of data scientists embedded in cross-functional squads across the Planning organization.
  • Define and communicate the long-term Data Science roadmap for agentic AI within Planning.
  • Drive the design and deployment of multi-agent workflows using orchestration frameworks such as LangGraph, ensuring scalability, reliability, and measurable business impact.
  • Partner with Product, Engineering, and stakeholders to align agentic AI capabilities with planner workflows and business objectives.
  • Establish best practices for experimentation, evaluation, and monitoring of agent-based systems (including causal tracing, benchmarking, and safety checks).
  • Mentor and grow the Data Science team, fostering technical excellence, collaboration, and an iterative, prototype-driven culture.


Requirements


  • 8+ years of experience designing and deploying applied ML or AI systems into production, with at least 3+ years leading data science teams.
  • Fluent in Python and a strong interest in general software engineering principles.
  • You have worked with common python frameworks (Numpy, Pandas…)
  • Demonstrated expertise with agentic AI systems, including orchestration frameworks (LangGraph preferred, LangChain or similar also considered).
  • Strong foundation in classical machine learning and applied modeling techniques, including regression, classification, clustering, and practical experience with models used in econometrics or marketing measurement.
  • Experience with agile development methodologies, such as Scrum or Kanban.


Preferred Qualifications


  • Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
  • Familiarity with DevOps practices and tools for continuous integration and deployment.
  • Solid understanding of system design principles, scalability, and performance optimization.



Acxiom is a customer intelligence company that provides data-driven solutions to enable the world’s best marketers to better understand their customers to create better experiences and business growth. A leader in customer data management, identity, and the ethical use of data for more than 50 years, Acxiom now helps thousands of clients and partners around the globe work together to create millions of better customer experiences, every day. Acxiom is a registered trademark of Acxiom LLC and is part of The Interpublic Group of Companies, Inc. (IPG). For more information, visit Acxiom.com.

Related Jobs

View all jobs

VP Data Science

VP Data Analytics (Fixed Term Contract)

VP of Data Strategy and Transformation

Head of Data Analytics

Head of Data Analytics

Senior Data Analyst

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.

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

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.