Data Engineering and Science Platformer; entry level

Data Science & Engineering Plat former About Havas Media

Havas is one of the world’s largest global communications groups, employing over 20,000 people in over 100 countries around the world. Our ambition is to be the UK’s most integrated, agile media and marketing services group with data, content, and entertainment at our core. It’s an exciting time for Havas Group in the UK, based in the Havas Village, known as HKX, in King’s Cross, London.

This sees all UK agencies and 1,700 people come together under one roof, with one common purpose to further our #Havas Together mantra, bringing media and creative together. Havas agencies stretch across media, creative, CRM, PR, healthcare, entertainment, and include among others Havas Media, Havas London, Havas Sports & Entertainment and Havas Helia. Havas Media have also recently launched CSA - a global consultancy, data science and analytics brand.

This role sits under the CSA brand in Havas Media Groups Data and Analytics (DNA) team.

Our DNA team is at the core of the Havas Media proposition, providing marketing analytics, data science & engineering, consumer insight and Martech consultancy. Working closely together with our account teams, the DNA team’s work allows clients to understand their customers, optimise their marketing investment plans and grow their brands. Within the Havas Data Science and Engineering team, we build the in-house tools and services that power data-driven marketing across the group.

We work primarily in Python and SQL, on Google Cloud Platform, developing everything from data pipelines to analytics platforms. As an agency, our work directly supports the strategies and campaigns behind some of the world’s best-known brands, so what we build has real, visible impact.

This role is open to anyone who can demonstrate real, genuine interest in data and technology - you don't need to come in as a finished technical expert, but you do need curiosity, drive, and a willingness to learn.

• Curiosity about data and technology
• A strong numerical and analytical mindset, whether developed through formal study or self-directed learning
• Enthusiasm for using data science and engineering to help drive smarter business decisions
• A keen interest in media and entertainment, as well as how data can shape audience insights and marketing strategies
• Interest in using Python and SQL for data manipulation, analysis, and automation (this can be through coursework, personal projects, or self-teaching - we’re happy to help you build on it)
• Willingness to learn data engineering tools and workflows
• Experience with statistical or analytical tools (e.g. R, pandas, Num Py, or visualization libraries) is a bonus, not a requirement
• Comfort with Excel for quick data analysis and PowerPoint for communicating insights effectively

• Contribute throughout the data product lifecycle, from data collection and transformation to analysis, modeling, and deployment.
• Be involved in designing and maintaining data pipelines to ensure reliable and efficient data flow across various systems and projects.
• Work to support model development for audience insights and media performance measurement.
• Collaborate with the team and contribute to developing data-driven tools or internal applications that enhance business decision-making.
• Work closely with Client Planning, Data Ops, Consumer Research & Insight, and Data Strategy teams to turn data into actionable recommendations and compelling stories for clients and stakeholders.
• Gain exposure to cloud platforms (such as AWS, GCP, or Azure); familiarity is helpful but not essential—curiosity and willingness to learn are key. We don’t expect you to have deep experience yet, but we’re looking for someone eager to grow and learn. You’ll gain hands-on experience with real-world data, engineering workflows, and analytical techniques as part of your day-to-day work.

• Extract, process, and transform large and varied datasets from multiple sources, ensuring data accuracy, consistency, and readiness for analysis.
• Conduct data analysis and…