Senior Data Scientist
Posted on 9 November 2026
£75,000 – £85,000
Permanent
Bedfordshire
Data, Analytics & AI
33439
Opportunity description
Job Title:
Senior Data Scientist
Senior Data Scientist
Department: Technology
Reports to: Head of Data, Analytics & AI
Location: Bedfordshire (1 day per week in office)
Base Salary: £75,000 – £85,000 plus bonus and other benefits
Contract: Permanent, Full-Time
Stanton House is partnering with a private equity-backed business currently undergoing a significant transformation programme looking to appoint a senior data scientist to lead the development of advanced analytical and machine learning solutions within a growing data function.
Role Overview
This is a highly business-facing role, working closely with stakeholders across the organisation to identify opportunities where data science can improve decision-making, optimise processes, and deliver measurable commercial value.
The successful candidate will take ownership of the end-to-end modelling lifecycle, from problem definition and experimentation through to validation, deployment support, and ongoing performance assessment. They will act as a trusted adviser to the business, translating complex analytical outputs into actionable recommendations and ensuring models are robust, defensible, and aligned with business objectives.
Responsibilities
Essential
Department: Technology
Reports to: Head of Data, Analytics & AI
Location: Bedfordshire (1 day per week in office)
Base Salary: £75,000 – £85,000 plus bonus and other benefits
Contract: Permanent, Full-Time
Stanton House is partnering with a private equity-backed business currently undergoing a significant transformation programme looking to appoint a senior data scientist to lead the development of advanced analytical and machine learning solutions within a growing data function.
Role Overview
This is a highly business-facing role, working closely with stakeholders across the organisation to identify opportunities where data science can improve decision-making, optimise processes, and deliver measurable commercial value.
The successful candidate will take ownership of the end-to-end modelling lifecycle, from problem definition and experimentation through to validation, deployment support, and ongoing performance assessment. They will act as a trusted adviser to the business, translating complex analytical outputs into actionable recommendations and ensuring models are robust, defensible, and aligned with business objectives.
Responsibilities
- Partner with senior stakeholders to identify and prioritise opportunities for advanced analytics and machine learning.
- Translate business challenges into analytical and modelling problems.
- Design, build, test and validate machine learning and statistical models across a range of use cases including forecasting, optimisation, classification, segmentation and recommendation.
- Apply appropriate validation techniques, benchmark performance, and communicate model limitations and uncertainty.
- Design and analyse experiments, pilots, and A/B tests to support evidence-based decision making.
- Provide analytical insight and decision support on strategic and commercial initiatives.
- Collaborate with data engineering, analytics and product teams to ensure solutions are scalable and production-ready.
- Establish and maintain best practices for model development, validation, governance and documentation.
- Monitor model performance and support the investigation of issues in production environments.
- Promote responsible AI practices, including bias testing, transparency and compliance with governance requirements.
- Contribute to the growth of the data function through mentoring, knowledge sharing and participation in hiring activities where required.
Essential
- Proven experience delivering data science solutions into production environments that have generated measurable business impact.
- Strong expertise in statistics, machine learning, model selection and validation methodologies.
- Experience developing predictive, forecasting, optimisation, classification or recommendation models.
- Advanced Python and SQL skills.
- Experience working with version-controlled codebases and collaborative development practices.
- Ability to communicate complex analytical concepts to non-technical and senior stakeholders.
- Experience designing and interpreting experiments and controlled trials.
- Strong commercial awareness and ability to assess the value and feasibility of analytical opportunities.
- Ability to operate independently within a developing or growing data capability.
- Experience working within cross-functional, product-led teams.
- Experience within large-scale consumer, retail, hospitality, logistics or operationally complex environments.
- Knowledge of causal inference, uplift modelling and experimentation techniques.
- Experience with demand forecasting, resource optimisation, pricing or inventory-related analytics.
- Familiarity with modern cloud data platforms, orchestration tools and BI technologies.
- Understanding of operational, transactional and customer behavioural data.
- Experience establishing data science standards or mentoring other practitioners.
