Senior Data Scientist
Manchester (Hybrid – 2 days onsite)
Up to £85,000 + bonus and Benefits
The Opportunity
This is a high-impact role within a growing SaaS organisation building a next-generation decisioning platform used by enterprise customers across multiple markets.
You’ll be joining at a pivotal moment — moving from project-based analytics to a product-led intelligence capability, where data science directly shapes commercial outcomes, not just dashboards.
The core focus is a recommendation and optimisation engine — a product that enables users to make high-value, high-frequency decisions with confidence. Getting the models right — and proving they work — is critical.
If you’ve ever been frustrated building models that never make it into production, this is the opposite environment.
What You’ll Be Doing
* Designing and deploying production-grade machine learning models that directly influence commercial decisions
* Building recommendation and optimisation systems across pricing, segmentation, and behavioural modelling
* Developing measurement frameworks to prove real-world impact (not just theoretical accuracy)
* Creating explainable outputs that non-technical users trust and act on
* Working closely with Product, Engineering, and Data to ensure models land and drive outcomes
* Acting as a senior voice within the team — raising standards, reviewing work, and shaping best practice
What We’re Looking For
* Strong experience in machine learning / statistical modelling in production environments
* Proven track record of building models that are deployed, monitored, and used
* Experience working in commercial / product-led environments (not just research or analysis)
* Ability to operate with autonomy — breaking down problems and delivering at pace
* Strong communication — able to translate complex outputs into clear business impact
Nice to have:
* Experience with pricing, optimisation, or recommendation systems
* Familiarity with explainable AI techniques (e.g. SHAP, feature importance)
* Exposure to MLOps / model lifecycle tooling (Databricks, MLflow, etc.)
The Environment
* Modern data stack and tooling (lakehouse architecture, ML pipelines, AI-assisted development)
* Product-led culture — models are expected to ship and deliver impact
* Close collaboration between Data, Product, and Engineering
* Backed by strong investment and a clear roadmap
Why Join
* Work on genuinely complex, high-value problems
* Build models that are actually used day-to-day
* Join a team at an inflection point — where you can shape direction, not just contribute
* Clear progression as the function scales