Data Scientist

VML MAP; Madrid; Presencial; EUR 45.000 - 65.000; Jornada completa

Descripción de la vacante

A leading data and AI solutions provider is seeking a Data Scientist in Madrid. This hands-on role involves developing and deploying predictive models and conducting deep customer analytics to drive business impact. Candidates should have a strong statistical foundation, hands-on machine learning experience, and proficiency in Python and SQL. The position emphasizes collaboration with cross-functional teams to deliver client-focused solutions. Ideal for pragmatic problem-solvers with a production-aware mindset.

Formación

• Strong understanding of inferential statistics, hypothesis testing, regression analysis, and experimental design.
• Hands-on experience building propensity models, lookalike models, customer segmentation, and churn prediction.
• Ability to connect analytical work to business outcomes and communicate value.

Responsabilidades

• Develop and deploy predictive models for targeted campaigns.
• Conduct deep customer analytics for actionable insights.
• Implement machine learning solutions ensuring production-readiness.

Conocimientos

Statistical intuition

Machine learning

Python

SQL

Data exploration

Collaboration

Herramientas

GCP Vertex AI

Salesforce Einstein

Adobe Sensei

Airflow

Terraform

Git

Descripción del empleo

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.