We're putting together a talented team to build the #1 training platform for Runners

We help everyday runners become outstanding by providing world-class training, coaching and community for everyone, whether you're improving your 5k time or training for your first marathon. To date we have built iOS, Android and Apple watch apps that help people achieve their goals by coaching them through the full journey and syncing to their favourite fitness devices.

We’re growing extremely fast! in November 2023 we closed a £5M funding round led by JamJar with participation from Eka Ventures, Venrex and Creator Ventures. In 2024, we were selected by Apple as one of three global finalists for the 2024 iPhone App of the Year, reflecting the innovation and impact of what we’ve built & now in 2025 we have ****just been acquired by Strava! 🤯 🎉

We want to grow as fast as we can into the future and are looking for individuals who will help us get there. Our aim is to reach millions of subscribers and be the go-to training platform for any runner. Now is a magical time to join and with our recent acquisition it makes the journey even more exciting! 🚀

Who we’re looking for

We are looking for a talented, hands-on, and experienced problem solver to join our highly skilled cross-functional engineering team as our first Data Scientist focusing on Marketing Analytics. In this role, you will work closely with our growth, product, and engineering teams to analyze user behaviour, optimise marketing strategies, and drive data-informed decisions that enhance user acquisition and retention. You will collaborate directly with our Head of Growth and CTO to help shape the future of Runna, receiving support throughout this exciting journey.

As a Data Scientist (Marketing), your role will include:

• Data Modelling: Help develop and optimise predictive models to forecast user engagement and lifetime value. These models will guide our decision making, helping us acquire the right users and maximise ROI.
• Marketing Measurement: You will have full ownership of our marketing measurement strategy from attribution modeling to incrementality testing – ensuring we have a crystal-clear view of what drives performance across our marketing mix
• Data Analytics: Analyse large datasets to extract actionable insights on user behaviour, marketing campaign performance, and customer segmentation.
• Marketing Optimisation: Collaborate with the performance marketing team to design and evaluate A/B tests, Lift Studies and Incrementality testing that will optimise customer acquisition channels, and improve conversion rates. Provide data-driven recommendations to enhance marketing ROI.
• Continuous Improvement: Stay abreast of industry trends, emerging technologies, and best practices in data science and marketing analytics. Propose and implement improvements to existing data processes and methodologies, working with engineering to drive automation.

What experience we’re looking for

If you don’t quite meet all of the below skills, we’d still love to hear from you as we might be able to tweak the role slightly or offer you a position better suited for you. You can apply directly below or contact us if you’re still unsure.

Your key experience:

• 3+ years of experience in data science, with a focus on marketing analytics or a similar role.
• Strong statistical analysis and modeling skills. Experience with A/B testing, cohort analysis, and predictive modeling techniques.
• You’ve had experience or lead the development of a pLTV model

Your key skills:

• Proficiency with Python programming
• Proficiency with SQL and experience with relational databases (e.g. Amazon Redshift, Snowflake) and bonus points if you have experience with NoSQL databases (e.g. DynamoDB), and graph databases (e.g. Amazon Neptune)
• Familiarity with analytics tools across the modern data and MarTech stack (e.g. SQL, python, Jupyter Notebooks, BI tools, Google Tag Manager, Mixpanel, Looker)
• Understanding of digital marketing channels, metrics, and strategies. Experience analysing data from various marketing platforms (e.g., Meta, Google Ads, Google Analytics).