Senior Data Scientist

As a Senior Data Scientist, you’ll take ownership of developing and improving production machine learning models used to support pricing and commercial decision-making.

You’ll partner closely with commercial, product, finance and engineering teams to identify opportunities, design experiments and deliver solutions that generate measurable business impact.

This role combines advanced modelling with hands-on deployment, making it ideal for someone who enjoys taking ideas from concept through to production., * Develop and optimise pricing and revenue-focused machine learning models.

• Design and evaluate experiments, including backtesting and online testing methodologies.
• Build predictive models to support commercial decision-making and risk assessment.
• Deploy, monitor and maintain production machine learning solutions.
• Work closely with stakeholders to understand business challenges and translate them into scalable data products.
• Develop and improve AI-powered solutions, including LLM and automation use cases.
• Drive best practices in model development, testing, monitoring and governance.
• Mentor colleagues and contribute to the wider technical direction of the team.

You’ll be a strong fit if you have:

• Several years’ experience building and deploying machine learning models in production environments.
• Strong experience in pricing, optimisation, revenue management or commercially focused analytics.
• Advanced Python and SQL skills.
• Experience designing and evaluating experiments and understanding statistical performance.
• A strong understanding of machine learning techniques and predictive modelling.
• Experience working within cloud environments such as Azure, AWS or GCP.
• The ability to clearly communicate technical concepts to both technical and non-technical audiences.
• A proven track record of turning business problems into measurable outcomes.

Nice to Have

• Experience with Bayesian modelling, optimisation algorithms or multi-armed bandits.
• Exposure to Generative AI, LLMs or agentic AI systems.
• MLOps experience, including CI/CD, model monitoring and deployment pipelines.
• Experience working within insurance, fintech, travel, ecommerce or other highly transactional environments.

• Opportunity to work on genuinely business-critical machine learning problems.
• High levels of ownership and autonomy.
• Exposure to both traditional machine learning and emerging AI technologies.
• A collaborative and highly technical environment.
• Clear opportunity to influence product direction and commercial outcomes.
• Competitive salary, bonus and benefits package.