Pozuelo de Alarcón (Madrid) | Hybrid model

Working hours: 9:00 AM – 6:00 PM

Permanent contract

About the role
Within the HR, Comms & ESG Transformation Office, we are looking to hire a junior profile with a strong interest in data modelling, machine learning, predictive modelling, and artificial intelligence, who is eager to take part in transformation initiatives applied to Human Resources, Communications and ESG. You will work with large volumes of data and global tools and data platforms, within an international environment (present in more than 18 countries), contributing to the development of models that directly impact business decision-making.

What will your mission be?
Design, develop, and implement data models and predictive models, applying artificial intelligence techniques to optimize HR, Comms & ESG processes.

Key responsibilities

Design and implementation of data models and predictive models in HR

Application of Artificial Intelligence techniques to people-related processes

Analysis and exploration of large data sets

Automation of analytical processes and solutions





Development of data mining initiatives

Generation of actionable insights for the business

Collaboration with international teams on transformation projects

Requirements

Degree in Data Science, Data Analytics, Mathematics, Statistics, or similar

1–3 years of experience in data analytics or modelling

Technical skills:

Python and SQL

Data modelling and/or machine learning

Advanced Excel

Power Automate / Power Apps

Cloud environments (ideally AWS / Bedrock)

AI skills (be familiar with concepts such as Markdown, Orchestrator, etc.)

Native Spanish

Fluent English (international working environment)

Nice to have

Professional experience in predictive modelling

Exposure to complex data environments (data warehouse, HR data, etc.)

What we offer

Opportunity to join a strategic transformation project

International environment with general collaboration

Hybrid working model (

📌 Junior Data Modelling (Madrid)
🏢 Verisure
📍 Madrid