Senior Data Scientist

Barcelona
1 week ago
Create job alert

A world class Tech Organisation are looking for a Senior Data Scientist to join their division in Barcelona on a hybrid basis - opportunity to join a really innovative environment where you'll work with cutting edge technologies.

The company:

The organisation have been running very successfully now for over twenty years and are recognised as market leaders in their sector. They have a global footprint, and their products are used by millions of users every single day.

They are entering a really exciting period of growth, and are recruiting for a number of new positions to the business as they've got pretty big plans for the next few years - so it's genuinely a great time to join.

They thrive on a positive and welcoming culture making it a great place to work, so it probably comes as no surprise that they have really low attrition rates, as so many of their staff members have long and successful careers with the business.

The role:

You'll be joining a multi-disciplinary squad of roughly seven consisting of Software Engineers, Data Engineers and Data Scientists, and will be tasked to ensure the deployment, monitoring and scaling of solutions in live product environments.

You'll be involved in the entire data science lifecycle, from defining problems and exploring data to developing and evaluating models. You'll also collaborate with cross-functional teams, including Engineers and Product Managers to help improve their offerings, particularly in the advertising space.

Within this role you'll also be involved in future planning of projects where you'll gain exposure to researching new modelling approaches, design experiments, scoping out new projects, prototyping and you'll also be regularly involved in assess their current product effectiveness to try and drive improvements.

Key Skills and Experience

** Prior experience within a Data Science role

** Python and SQL

** Data tools (ideally Spark and Apache Airflow)

** Working with Large Language Models

** MLOps

** Infrastructure as code tools (Kubernetes, Docker etc)

** Cloud Services (ideally AWS)

** Experience within AdTech would be really desirable for this role

Useful information:

Their offices are based in central Barcelona where they support hybrid working, you'll be expected onsite about twice a week, however they are really flexible about what days.

They're offering a very competitive salary from €70,000 - €95,000, depending on experience with great benefits to match (which include multiple bonuses and more!).

If you're keen to find out more, please reach out to Matthew MacAlpine at Cathcart Technology

Related Jobs

View all jobs

Senior Data Scientist

SENIOR DATA SCIENTIST - Computer Vision / Generative AI HYBRID

Senior Data Scientist (GenAI)

Senior Data Scientist (MLOps)

Senior Data Scientist/ Senior Risk Scientist

Senior Data Scientist - Insurance

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Top 10 Machine Learning Career Myths Debunked: Key Facts for Aspiring Professionals

Machine learning (ML) has become one of the hottest fields in technology—touching everything from recommendation engines and self-driving cars to language translation and healthcare diagnostics. The immense potential of ML, combined with attractive compensation packages and high-profile success stories, has spurred countless professionals and students to explore this career path. Yet, despite the boom in demand and innovation, machine learning is not exempt from myths and misconceptions. At MachineLearningJobs.co.uk, we’ve had front-row seats to the real-life career journeys and hiring needs in this field. We see, time and again, that outdated assumptions—like needing a PhD from a top university or that ML is purely about deep neural networks—can mislead new entrants and even deter seasoned professionals from making a successful transition. If you’re curious about a career in machine learning or looking to take your existing ML expertise to the next level, this article is for you. Below, we debunk 10 of the most persistent myths about machine learning careers and offer a clear-eyed view of the essential skills, opportunities, and realistic paths forward. By the end, you’ll be better equipped to make informed decisions about your future in this dynamic and rewarding domain.

Global vs. Local: Comparing the UK Machine Learning Job Market to International Landscapes

How to evaluate opportunities, salaries, and work culture in machine learning across the UK, the US, Europe, and Asia Machine learning (ML) has rapidly transcended the research labs of academia to become a foundational pillar of modern technology. From recommendation engines and autonomous vehicles to fraud detection and personalised healthcare, machine learning techniques are increasingly ubiquitous, transforming how organisations operate. This surge in applications has fuelled an extraordinary global demand for ML professionals—data scientists, ML engineers, research scientists, and more. In this article, we’ll examine how the UK machine learning job market compares to prominent international hubs, including the United States, Europe, and Asia. We’ll explore hiring trends, salary ranges, workplace cultures, and the nuances of remote and overseas roles. Whether you’re a fresh graduate aiming to break into the field, a software engineer with an ML specialisation, or a seasoned professional seeking your next challenge, understanding the global ML landscape is essential for making an informed career move. By the end of this overview, you’ll be equipped with insights into which regions offer the best blend of salaries, work-life balance, and cutting-edge projects—plus practical tips on how to succeed in a domain that’s constantly evolving. Let’s dive in.

Machine Learning Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Machine learning (ML) has become an indispensable force in the modern business world, influencing everything from targeted marketing campaigns to advanced medical diagnostics. As industries integrate predictive algorithms and data-driven decision-making into their core operations, the need for effective leadership in machine learning environments has never been greater. Whether you’re overseeing a small team of data scientists or spearheading an enterprise-scale ML project, your leadership style must accommodate rapid innovation, complex problem-solving, and diverse stakeholder expectations. This guide provides actionable insights into how you can motivate, mentor, and establish achievable goals for your machine learning teams—ensuring they thrive in data-driven environments.