Data Scientist

Blue Light Card. Individually great, together unstoppable

At Blue Light Card, our members are at the centre of everything we do. The Data Scientist team builds the algorithms and models that help us understand member behaviour, anticipate their needs, and keep our members engaged with the platform.

We’re looking for a Data Scientist, Decision Sciences, with a focus on retention and member engagement. You'll evaluate pipelines and results of retention models and identify improvements in outputs to improve the retention strategy. You'll partner closely with stakeholders across the organisation, translating complex questions into well‑designed solutions, and communicating your findings in ways that land with both technical and non‑technical audiences alike.

• Design, develop, and iterate on machine learning models across the member lifecycle, with a particular focus on retention, churn prediction, and customer lifetime value
• Evaluate existing model pipelines and outputs, identifying and implementing improvements to increase accuracy and business impact
• Work closely with the CRM Lifecycle team to connect model outputs to retention strategies, capturing feedback and incorporating it back into model development
• Build forecasting models and marketing mix models to support financial planning and commercial decision‑making
• Translate ambiguous business problems into well‑defined data science approaches, conducting deep‑dive analyses across member behaviour, commercial performance, and marketing effectiveness
• Build and interpret A/B tests and holdout experiments to support evidence‑based decision‑making
• Create dashboards and visualisations that help the wider organisation understand model results and progress
• Act as a trusted partner to business and analytics stakeholders, understanding their goals and proactively identifying where data science can add value

• Significant experience as a Data Scientist, with a background in marketing analytics, ecommerce, or a loyalty or membership‑driven environment
• Strong Python proficiency for data manipulation, statistical modelling, and machine learning, alongside advanced SQL skills and experience with dbt
• Solid grounding in statistical methods including regression, causal inference, and experimental design, with hands‑on experience building and interpreting A/B tests
• Practical experience building predictive models, particularly in retention or customer engagement contexts, with working knowledge of MLOps practices and model deployment pipelines
• Experience collaborating with CRM or lifecycle marketing teams, with the ability to shape model outputs into actionable recommendations
• The ability to communicate complex findings clearly to non‑technical stakeholders, and to build reusable data products that others can act on independently
• Familiarity with CLV modelling frameworks such as BG/NBD, Pareto/NBD, or ML‑based approaches would be a bonus, but is not essential

Our mission is simple – make heroes happy. Our members are the real‑life heroes who keep us all safe, cared for, and thriving. It's what gets us up in the morning and pushes us to go further, think bigger, and create something that truly matters. By focusing on their happiness, we create amazing experiences, deliver unrivalled discounts, innovative products, and world‑class service.

We don't just follow the usual path - we look for smarter, bolder ways to deliver real impact. We take ownership, move fast, and work shoulder to shoulder to build something special.

We're committed to building a diverse and inclusive team where everyone feels they belong. Different perspectives and experiences help us grow, innovate, and better reflect the communities we serve.

We promote hybrid working, and value in‑person collaboration so encourage time in our offices, where you can make the most of our fully stocked snack drawers – either the HQ in Leicestershire, or London, Holborn office. The frequency and office location will vary depending on the role and team. We aim to be flexible, but we aren't able to offer fully remote working.

• Hybrid working and flexible hours
• E…