Design, build, and own a robust A/B testing and experimentation framework for the growth function
Define metrics, set up holdout groups, run significance tests, and communicate results with clarity to both technical and non-technical stakeholders
Identify opportunities for rapid iteration and champion a test-and-learn culture across the growth pod
Build and maintain scalable data pipelines and databases that support real-time and near-real-time growth analytics
Develop ETL pipelines (e.g. Python-based) and ensure reliable, clean data flowing into dashboards and models
Collaborate with the Head of Data Engineering to align on tooling, architecture, and best practices
Analyse user behaviour across the full funnel — acquisition channels, onboarding, conversion, engagement, and churn
Build models and dashboards that surface actionable insight for the growth and marketing teams
Work closely with AI tools and emerging technologies; bring demonstrable experience of AI-native workflows to the team
Act as the primary data partner for growth PMs, engineers, and marketing stakeholders
Translate complex analyses into clear narratives and recommendations for senior leadership
Over time, help define what a best-in-class data science function looks like and contribute to building it

Master’s degree in a quantitative discipline (e.g. Statistics, Computer Science, Mathematics, Engineering) or equivalent practical experience
4
6+ years of experience as a data scientist, ideally within a growth pod or growth-focused team at a scale-up (Series B through pre-IPO)
Hands-on experience building and running A/B testing frameworks from scratch
Strong engineering fundamentals — comfortable building ETL pipelines, data models, and production-quality analytical code (Python preferred)
Experience working with complex, cross-functional data in a fast-paced startup or scale-up environment
AI-native: actively using AI tools in your day-to-day workflow and able to speak to the tangible impact this has had
Comfortable operating autonomously with a builder mindset — there is no established data science function to lean on

Flexible working hours and a vibrant company culture
Remote work
Plenty of opportunities for growth and learning
Unlimited holiday allowance
Chance to join and contribute to a company during its exponential expansion phase

Data Scientist – Growth

Key skills