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.
Benefits
- 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
Tags & focus areas
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