Data Science Lead

Salary: £95,000-£100,000 + bonus and benefits

Location: Basingstoke — hybrid working, with 2-3 days per week onsite

The Opportunity

ShareForce is seeking a hands‑on Data Science Lead to take ownership of four established predictive models and build a mature, self-sufficient internal data science capability. This newly created leadership role will oversee the transfer of technical knowledge and ownership from a specialist external partner, strengthen model management and governance, and develop the internal team as the function grows.

Combining deep technical expertise with strategic leadership, you will shape the organisation's data science, AI and external data strategies within a Microsoft Azure and Databricks environment. You will advise senior stakeholders, translate complex technical matters into clear commercial decisions, and contribute credible evidence of progress and value to strategic and due diligence discussions.

Key Responsibilities

• Take end-to-end ownership of four predictive models, covering development, validation, deployment, monitoring, documentation and optimisation.


• Remain technically hands‑on, working directly with data, code and modelling tools to resolve issues and improve model performance.


• Lead the transfer of knowledge, capability and technical ownership from an external specialist partner into the internal team.


• Define and deliver a data science roadmap aligned with customer, commercial and operational priorities.


• Establish effective standards for model development, governance, explainability and lifecycle management in a regulated environment.


• Help shape the Microsoft Azure and Databricks data science environment, including the organisation's approach to deploying and managing machine‑learning models.


• Develop practical AI and external data strategies, prioritising opportunities supported by clear business cases.


• Build and develop the internal data science capability, assuming broader leadership responsibility as the function grows.


• Advise senior stakeholders and translate technical findings into clear, commercially focused recommendations.


• Support strategic and due diligence discussions by articulating the organisation's capability, progress, governance and future roadmap.

Skills and Experience

• Significant, demonstrable experience in data science, machine learning, predictive modelling or a closely related discipline.


• Deep practical expertise across the complete model lifecycle, from data preparation and development through to deployment and production monitoring.


• Strong Python and SQL skills, with experience of modern, cloud‑based data environments.


• Practical experience with Databricks and Microsoft technologies, particularly Microsoft Azure.


• A strong track record of owning and improving production models and connecting model performance to measurable business outcomes.


• Experience establishing model‑management and governance practices within a growing or developing data science function.


• Substantial experience in regulated financial services, insurance or a comparable regulated sector.


• Consulting experience, or an equivalent ability to diagnose complex problems, advise senior stakeholders and translate strategy into delivery.


• Experience managing specialist partners and transferring externally held knowledge and capability into an internal team.


• Strong leadership, commercial judgement and stakeholder‑management skills.


• The willingness and technical ability to remain actively involved in hands‑on data science work.

Package and Working Arrangements

• £95,000-£100,000 base salary.


• Performance-related bonus.


• Hybrid working from the Basingstoke office, with an expectation of 2-3 days onsite each week.


• 25 days' annual leave plus bank holidays.


• Pension and wider benefits package.

ShareForce is committed to creating an inclusive recruitment process. Applications are welcomed from candidates of all backgrounds who can demonstrate the experience and potential required for the role.