Your work will sit close to commercial decision-making. You’ll help teams understand customer behaviour, improve targeting, shape product and marketing decisions, and spot where data can unlock growth.

You’ll get plenty of ownership. You’ll lead analytics projects, manage stakeholder conversations, and turn complex data into clear recommendations. The team needs someone who can get moving quickly, ask sharp questions, and explain the “so what?” behind the model output.

What You’ll Be Doing

• You’ll personally build propensity models to predict customer behaviour.
• You’ll create customer segmentation models to support targeting and personalisation.
• You’ll use SQL to query and prepare large datasets independently.
• You’ll assess model performance and explain what the results mean.
• You’ll translate model outputs into practical recommendations for Product and Marketing teams.
• You’ll manage stakeholder conversations while staying close to the technical work.

What You’ll Need

• You’ll need proven hands-on experience building propensity models.
• You’ll have a background in data science, statistics, mathematics, physics, economics, engineering or another numerate discipline.
• You’ll be strong with SQL and comfortable working with large customer datasets.
• You’ll have 4+ years’ experience in analytics, data science or customer modelling.
• You’ll be confident explaining modelling decisions and model performance to non-technical stakeholders.

Useful Experience

• Customer lifetime value modelling.
• Churn or decay modelling.
• Marketing attribution.
• A/B testing.
• Next best action or personalisation.

Interview Process

CV review > recruiter call > client submission > client interview process > offer

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