About The Role

Want to solve data science problems most companies can’t touch?

We’re looking for a Data Scientist to join an innovative, fast-growing data science business in a highly technical team environment. This is a rare chance to work on challenging, real-world problems using Bayesian statistics, machine learning, and scientific rigor—the kind of work that goes beyond dashboards and into true modeling and inference.

Founded as a spin-out from a world-leading university research group, the company brings academic depth and practical delivery together. If you enjoy building models, testing hypotheses, and turning uncertainty into actionable insights, this role was made for you.

What You’ll Do

As a Data Scientist, you’ll help design, develop, and deploy data-driven solutions across complex modeling and analytics challenges. You’ll collaborate closely with engineers and domain experts, translating ambiguous questions into robust, measurable outcomes.

• Apply Bayesian statistics to build probabilistic models that capture uncertainty and improve decision-making
• Develop and productionize machine learning solutions using sound experimental methodology
• Work on scientific and research-led approaches to modeling, inference, and evaluation
• Design experiments, evaluate model performance, and iterate based on results and stakeholder needs
• Collaborate with a highly technical team to refine problem framing, features, and modeling strategies
• Communicate findings clearly—sharing model insights, limitations, and recommendations with technical and non-technical partners
• Contribute to the improvement of data pipelines and analytical workflows where needed
• Maintain strong documentation and reproducibility across modeling work

What We’re Looking For

You don’t need to check every box—if you’re excited by complex modeling, enjoy learning, and want to work in a team that cares about quality, we want to hear from you.

• Proven experience as a Data Scientist (or equivalent) building and evaluating ML/statistical models
• Strong working knowledge of Bayesian methods and/or probabilistic modeling
• Practical experience with machine learning (modeling, validation, performance analysis)
• Comfort working with scientific-style problem solving—hypothesis-driven thinking and rigorous evaluation
• Strong programming skills (commonly Python-based data science environments)
• Experience using data to drive decisions, not just generate outputs
• Ability to clearly explain technical concepts, assumptions, and results
• A collaborative mindset—comfortable working with engineers and other technical stakeholders

Why This Role?

• Research-backed work: Spin-out heritage means you’ll use cutting-edge statistical approaches in real applications
• High technical standards: You’ll work with a team that cares about modeling quality, evaluation, and reproducibility
• Real impact: Your work will directly influence how decisions are made under uncertainty
• Growth opportunity: You’ll build deeper expertise across Bayesian statistics and ML in a supportive environment

Location & Working Pattern

• Hybrid working arrangement
• Herne Hill, South London

Salary & Package

• £54,000–£58,000 per annum (DOE)

Benefits

We care about building a team where people can do their best work. While benefits can vary, you can expect a role designed for long-term growth and support.

• Competitive salary aligned with experience
• Hybrid working flexibility
• Opportunity to work on challenging Bayesian/ML problems with a highly technical team
• Support for continuous learning and improvement through real projects

How to Apply

If you’re excited by Bayesian statistics, enjoy rigorous modeling, and want to work on problems that truly require depth—apply now. We’d love to see what you’ve built, what you’ve learned, and how you approach complex modeling challenges.

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