Data Scientist

Wunderman; Greater London; On-site; GBP 50,000 - 75,000; Full time

Job summary

A leading data and AI consultancy is seeking a Data Scientist to drive data-driven solutions for top-tier brands. You will leverage statistical methods and machine learning to create impactful analytics and models. The ideal candidate needs practical experience in deploying models, a solid foundation in statistics, and proficiency in Python and SQL. Collaboration with engineering teams is crucial for achieving production-ready outcomes. This role focuses on delivering measurable marketing value and customer experience improvements.

Benefits

Diverse work environment

Opportunities for growth

Collaborative team culture

Qualifications

• Experience with building prediction and recommendation systems.
• Hands-on path to production models beyond theory.
• Strong understanding of regression analysis and hypothesis testing.

Responsibilities

• Develop predictive models for marketing campaigns.
• Conduct customer analytics for actionable insights.
• Collaborate with Data Engineers for model deployment.

Skills

Statistical intuition

Data manipulation with Python

SQL for analysis

Machine learning experience

Data exploration skills

Business acumen

Version control with Git

Collaboration in cross-functional teams

Education

Solid statistical foundation

Tools

GCP Vertex AI

Salesforce Einstein

Adobe Sensei

Job description

We are seeking a Data Scientist to join our Data & AI practice. This is a role for a pragmatic problem-solver who can translate business challenges into data-driven solutions for world-renowned brands. You will apply statistical thinking and machine learning techniques to deliver predictive capabilities that drive measurable marketing and customer experience outcomes—and you'll be comfortable taking your models beyond the notebook into production environments.

What will your day look like?

This is a hands‑on role where you will deliver impactful analytics and machine learning solutions, primarily leveraging out‑of‑the‑box platform capabilities while applying solid statistical foundations to ensure rigorous, trustworthy results.

More specifically, your tasks will include:

• Developing and deploying predictive models (propensity, churn, lookalike) and recommendation systems for targeted campaigns and personalization.
• Conducting deep customer analytics (segmentation, LTV, behavioral analysis) to generate actionable insights.
• Implementing ML solutions using both platform‑native capabilities and custom development, ensuring models are production‑ready and AI‑consumable.
• Maintaining statistical rigor in all methodologies, from experiment design to model validation, supported by robust data exploration and preparation.
• Advising clients on data science opportunities, communicating complex findings clearly, contributing to repeatable solution frameworks, and fostering cross‑functional collaboration with engineering, strategy, and client services teams.

Who are you going to work with?

You will join a team of Data Scientists and Analysts who are passionate about turning data into business impact. You'll work closely with our Data Engineering team that builds the pipelines and infrastructure that power your models—and at times, you'll contribute directly to that work.

Beyond your immediate team, you will collaborate with stakeholders across our organization (strategy leads, account directors, creative teams) and directly with client marketing and analytics teams.

What do you bring to the table?

You are a practical, business‑minded data scientist who prioritizes delivering value over theoretical perfection. You have strong statistical intuition and can clearly explain analytical approaches and their limitations to both technical and non‑technical audiences. You're not just a notebook data scientist—you understand what it takes to get models into production.

• Solid statistical foundation: Strong understanding of inferential statistics, hypothesis testing, regression analysis, and experimental design. You don't need to derive algorithms from scratch, but you must understand when and why to apply them.
• Applied machine learning experience: Hands‑on experience building propensity models, lookalike/similarity models, customer segmentation, churn prediction, lifetime value models, and recommendation systems.
• Proficiency in Python and SQL for data manipulation, analysis, and model development.
• Production‑aware mindset: Understanding of what it takes to move models from experimentation to production. You're comfortable working with Data Engineers on deployment, and familiar with concepts like scoring pipelines, feature engineering workflows, and orchestration tools (e.g., Airflow, Terraform).
• Good engineering practices: Comfort with version control (Git), writing clean and maintainable code, and collaborating in shared codebases.
• Experience with cloud ML platforms: Familiarity with cloud‑based ML services (e.g., GCP Vertex AI) and/or marketing platform ML capabilities (Salesforce Einstein, Adobe Sensei).
• Data exploration skills: Ability to use visualization tools to inspect data, validate assumptions, and inform modeling decisions.
• Business acumen: Ability to connect analytical work to business outcomes and communicate value in terms clients care about. Agency or consulting experience is a strong advantage.
• Collaborative mindset: Comfort working in cross‑functional teams and partnering closely with engineers, strategists, and client stakeholders.

A leader in personalized customer experiences

VML MAP is a world‑leading Centre of Excellence that helps businesses humanize the relationship between the brand and the customer through hyper personalization at scale, marketing automation and CRM. With the brain of a consultancy, the heart of an agency and the power of technology and data, we work with some of the world's most admired brands to help them on their transformation journey to becoming truly customer‑centric. Together, we are 1000+ technology specialists, data scientists, strategic thinkers, consultants, operations experts, and creative minds from 55+ nationalities.

A global network

We are part of the global VML network that encompasses more than 30,000 employees across 150+ offices in 60+ markets, each contributing to a culture that values connection, belonging, and the power of differences.

#LI-EMEA

WPP (VML MAP) is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.