Location: London
Reporting To: Chief Technology Officer
About Us
Our client is a leading AI-powered SaaS company that helps businesses unlock the full potential of their first-party data. Their platform solutions transform complex data into actionable intelligence, enabling clients to drive customer revenue growth, optimise decision-making, and gain a competitive edge.
They specialise in key UK consumer service sectors, including Finance, Retail, Travel, Telco, and Healthcare, where AI-driven insights turn first-party data into a competitive advantage. Built on deep industry expertise from working with major household-name brands, their solutions tackle real-world commercial challenges with precision.
Currently serving clients in four countries, they have two live products and two cutting-edge AI solutions in development. These innovations, combined with deep industry expertise, position them to scale rapidly and deliver exceptional value.
This is an exciting moment in their journey as they scale rapidly, push AI-driven decision intelligence forward, and help businesses unlock sustainable growth.
Role Overview
We're looking for a Senior Data Scientist who can combine the rigour of statistical modelling with the creativity of real-world storytelling. You'll design and deliver AI/ML models that are not just accurate — but deployable, explainable, and aligned to clients' commercial goals.
You'll play a key role in shaping how AI is productised and scaled, from building bespoke datasets to operationalising end-to-end pipelines with ML Ops. Your work will span forecasting, customer segmentation, churn prediction, and commercial optimisation.
This is not a research role — it's a hands-on, high-impact position for someone ready to own data science delivery across a variety of projects and products.
Key Responsibilities
Design and build machine learning models for:
○ Forecasting (e.g. demand, revenue) using tools such as Prophet
○ Propensity modelling for churn, conversion, and cross-sell
○ Customer segmentation using k-means or advanced clustering techniques
Own end-to-end data workflows: feature creation, data wrangling, model tuning, validation, deployment, and monitoring
Architect your own datasets where needed — merging structured and semi-structured data to power robust insights
Operationalise models using ML Ops, ensuring continuous delivery and integration with cloud-based systems
Collaborate with product, engineering, and client teams to align technical outputs with business outcomes
Interpret and visualise results artistically and insightfully — transforming statistical outputs into compelling decision tools
Continuously experiment with new methods, technologies, and approaches to improve performance and interpretability
Lead by example on code quality, experimentation, and reproducibility
Coach and mentor junior data scientists
3-5 years of experience in a Data Science, AI, or ML-related role
Why Join?
Work on real-world AI challenges that impact millions of customer decisions
Join a cloud-native, AI-first company where models are deployed, scaled, and used — not just prototyped
Collaborate with senior AI engineers, product managers, and domain experts
Shape product and platform direction through your modelling and insight
Competitive salary, professional development budget, and mentorship from industry veterans
This is an opportunity to push the boundaries of applied data science in a company that doesn't just talk about AI — they build it, run it, and scale it.
If you're a builder, thinker, and creative technologist — we want to hear from you
Salary description
£75000.00 - £80000.00 per year