Data Platformer: Analytics, Pipelines & Insights

Havas; Greater London; Hybrid; GBP 60,000 - 90,000; Full time

Benefits offered by this job

Free breakfast in the office

Wellbeing support

Gym discount

Eye care

Cycle to work scheme

Season ticket loan

Employee assistance programme

Workplace Nurseries

Job summary

Havas Media in London is launching a Data Science & Engineering Platformer within the DNA team. The role focuses on data pipelines, analytics, and engineering workflows using Python and SQL on cloud platforms.

You’ll contribute to data-driven marketing insights for some of the world’s best-known brands in a hybrid office setting. The position aims to grow hands-on with real-world data, crossing collaboration with Client Planning, Data Ops, and Insight teams, while developing practical data

Qualifications

• Interest in data science and analytics.
• Fluent written and spoken English.
• Curiosity about data and technology and a willingness to learn.
• Ability to translate data into actionable insights for non-technical audiences.

Responsibilities

• Contribute across the data product lifecycle from collection to deployment.
• Design and maintain data pipelines for reliable data flow.
• Support model development for audience insights and media performance.
• Create data-driven tools and dashboards to inform client decisions.
• Collaborate with DNA, Data Ops, and Strategy teams to turn data into stories.

Skills

Python

SQL

Analytical mindset

Data storytelling

Excel

Pandas

NumPy

PowerPoint

Tools

Python

SQL

Excel

PowerPoint

Pandas

NumPy

Job description

Havas Media in London is launching a Data Science & Engineering Platformer within the DNA team. The role focuses on data pipelines, analytics, and engineering workflows using Python and SQL on cloud platforms.

You’ll contribute to data-driven marketing insights for some of the world’s best-known brands in a hybrid office setting. The position aims to grow hands-on with real-world data, crossing collaboration with Client Planning, Data Ops, and Insight teams, while developing practical data