Data Scientist

VML MAP; Greater London; On-site; GBP 45,000 - 65,000; Full time

Job summary

A leading data and AI consulting firm in Greater London is seeking a Data Scientist to deliver impactful analytics and machine learning solutions. Responsibilities include developing predictive models, conducting customer analytics, and advising clients on data opportunities. Ideal candidates have strong statistical foundations, applied machine learning experience, and proficiency in Python and SQL. This role offers the chance to collaborate with cross-functional teams and directly impact business outcomes across various projects.

Qualifications

• Solid statistical foundation in inferential statistics and regression analysis.
• Hands-on experience in customer segmentation and churn prediction.
• Comfortable with scoring pipelines and feature engineering workflows.

Responsibilities

• Develop and deploy predictive models for targeted campaigns.
• Conduct deep customer analytics to generate actionable insights.
• Advise clients on data science opportunities.

Skills

Statistical intuition

Python

SQL

Data exploration skills

Collaborative mindset

Applied machine learning experience

Tools

Cloud ML services

Visualization tools

Version control (Git)

Job description

Overview

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 who build 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.
• 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: Comfortable working with Data Engineers on deployment, familiar with scoring pipelines, feature engineering workflows, and orchestration tools (Airflow, Terraform).
• Good engineering practices: Comfortable 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 (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: Comfortable working in cross‑functional teams and partnering closely with engineers, strategists, and client stakeholders.

Equal Opportunity and Disability Self‑Identification

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.

You are welcome to complete our voluntary disability self‑identification form. The form is confidential and not used in hiring decisions. It is voluntary and you have the right to decline.