Responsibilities

Develop and deploy data science models to support key e-commerce use cases such a purchase propensities, marketing attribution, product recommendations and retention risk.
Design and analyse experiments (A/B and multivariate testing) to evaluate product and marketing initiatives.
Translate business problems into clear analytical questions and data science solutions.
Continuously monitor model performance and refine models to ensure accuracy and effectiveness in an evolving ecomms landscape.
Communicate insights and model outputs clearly to non-technical stakeholders, influencing decisions.
Collaborate with Data Engineers to ensure models are scalable, reliable and production ready.
Work closely with analysts to share best practice, provide coaching, and raise overall data capability across the team.
Support a culture of data-driven decision making across the business.

Basic qualifications

Degree in Data Science, Mathematics, Computer Science, or a related field.
Over 2 years data science experience ideally within an e-commerce, digital, or consumer business.
Ability to focus on business outcomes (growth, conversion, retention, margin), not just models — and to prioritise work that delivers measurable impact.
Confident in statistics, experimentation, and machine learning, with the judgement to choose the right level of complexity for the problem.
Understanding of customer behaviour, funnels, marketing channels, pricing, and product performance — or the ability to learn this quickly.
Can explain complex concepts simply, tell a compelling data story, and influence non-technical stakeholders to act on insights.
Works effectively with analysts, data engineers, product and marketing teams — building reusable, well-documented, scalable solutions and raising capability around them.
Excellent Python skills (e.g. pandas, numpy, scikit-learn, statsmodels) and strong expertise in SQL for data querying, manipulation, and transformation.
Familiarity with cloud data platforms (e.g. BigQuery, Snowflake, Databricks).
Excellent problem-solving skills.
Experience with recommendation systems, forecasting, or causal inference.
Knowledge of marketing analytics (attribution, MMM, incrementality).
Experience with data visualisation tools.
Understanding of version control using Git.

Company Equity- In return for helping us to grow, we’ll offer you company equity, meaning you own a piece of this business we are all working so hard to build.
25 days annual leave + Bank Holidays
1 extra day off for your Birthday
Employee Assistance Programme
Perks at Work benefit platform
Opportunities for career development and progression

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Fulltime Remote Data Science Ai