Data Scientist (Marketing)

Runna
London
1 week ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist - Remote

Data Scientist/Statistician

Data Scientist - Gen AI - Remote

Data Scientist - Gen AI - Remote

Data Scientist - Gen AI - Remote

Get AI-powered advice on this job and more exclusive features.

We help everyday runners become outstanding by providing world-class training, coaching and community for everyone, whether youre 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.

Were growing extremely fast and in November 2023 closed a new $6.5M 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 weve built. We want to grow as fast as we can into the future and are looking for individuals who will help us get there. For more about our background and growth check out our Careers Page!

Were now looking ahead to the future and the people who want to help us build and scale Runna. Our aim is to reach millions of subscribers in the next 5 years and be the go-to training platform for any runner. Now is a magical time to join, were still small, and everyone makes a foundational difference.

Who Were Looking For

We are looking for a talented, hands-on, and experienced problem solver to join our highly skilledcross-functional engineering teamas 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.

Requirements
What experience were looking for
If you dont quite meet all of the below skills, wed 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 youre 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.
  • Youve 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).
  • Ability to translate complex data insights into clear, actionable recommendations for non-technical stakeholders.
  • Analytical and detail-oriented, with a commitment to producing high-quality work.
  • Able to work within a highly-skilled engineering team in a fast-paced, iterative environment.

Bonus points if you:

  • Are able to quickly pick up new skills when necessary or are happy to step outside your comfort zone to try something new - such as implementing tracking pixels, building data pipelines, or stitching data together across disparate data sources.
  • Have experience working with a B2C subscription business model.
  • Have a strong interest in the health/fitness technologies.

Our tech stack
Below you can find a small reflection of our current tech stack:
Frontend:

  • React Native (iOS and Android).
  • Typescript.
  • GraphQL (Apollo Client).
  • Fastlane.
  • SwiftUI (Apple Watch).
  • Maestro E2E tests.

Backend:

  • Serverless (AWS).
  • Lambdas (NodeJS & Python).
  • AWS AppSync.
  • DynamoDB, S3, SQS, SNS, EventBridge, SageMaker.
  • Postman API tests.

All the other good stuff:

  • Sentry.
  • GitHub Actions.
  • Intercom, Mixpanel.
  • RevenueCat.
  • App Store Connect / Play Store.
  • Google Tag Manager.

Benefits
Benefits and options

  • Based on years of direct, relevant experience. Level IV £80-95k.

Well be growing our package of benefits over time. We currently offer:

  • Flexible working (we typically work 2-3 days in our office in Vauxhall).
  • Salary reviews every 6 months or whenever we raise more investment.
  • 25 days of holiday plus bank holidays.
  • A workplace pension scheme.
  • A brand new Macbook, a running watch of your choice, and anything else you need to do your best work.
  • Private health insurance.
  • Enhanced family care policy (3 months fully paid leave when a new Runna joins the family, fertility support & other benefits).
  • An hour slot each week (during work time) to do a Runna workout.

How to apply
To apply, please apply HERE and well take it from there!

  • Please let us know if theres anything we can do to better accommodate you throughout the interview process - this can be from scheduling interviews around childcare commitments to accessibility requirements. We want you to show your best self in the process.

Seniority level

  • Mid-Senior level

Employment type

  • Full-time

Job function

  • Engineering and Information Technology

Industries

  • Non-profit Organizations and Primary and Secondary Education

J-18808-Ljbffr

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.

Jobs

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Jobs Careers

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Jobs

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.