Data Science Manager (City of London)

Data Science Manager

Location: Hybrid (1–2 days/week in Reading or Central London)

Salary: £80,000-£100,000+ Car Allowance + 10% Bonus + Excellent Benefits

Recruiting on behalf of a major UK automotive technology group

We’re recruiting on behalf of one of the UK’s largest and most influential automotive groups for a Data Science Manager (Operations) . This is an outstanding opportunity for an experienced data scientist and people leader to shape operational strategy using cutting-edge optimisation techniques across a high-impact, data-rich organisation.

With a remit covering everything from vehicle logistics to refurbishment optimisation , this role is perfect for someone who’s passionate about delivering measurable business value through advanced modelling and hands-on leadership.

The Role

As Data Science Manager for the Operations team , you will lead a growing group of data scientists focused on solving real-world operational challenges. Your team will design and deploy advanced models that improve supply chain efficiency, optimise vehicle movement, and enhance operational workflows across the organisation.

You’ll be supported by a modern MLOps and Data Engineering function, giving you the time and tools to focus on innovation , model development , and strategic delivery .

This is a hybrid role , with flexibility to work from home most of the week and spend 1–2 days onsite in Reading or Central London .

Key Responsibilities

• Lead and mentor a data science team focused on operational optimisation, logistics, and refurbishment strategy.
• Define and deliver a product roadmap that solves key operational pain points through data science and algorithmic innovation.
• Apply advanced mathematical optimisation techniques (e.g., Linear Programming , Scheduling , Graph Theory ) to complex business problems.
• Work cross-functionally with senior stakeholders to translate business requirements into scalable technical solutions.
• Collaborate with MLOps and Engineering teams to productionise models using robust and scalable pipelines.
• Champion the integration of model outputs into wider data and reporting platforms.
• Clearly communicate technical insights and model outcomes to non-technical stakeholders across all levels.

Your Background & Skills

Required:

• Proven experience building optimisation models using Python libraries such as PuLP , ortools , or SciPy.optimize .
• Hands-on expertise in combinatorial optimisation , scheduling algorithms , network optimisation , and/or simulation methods (e.g., Monte Carlo, Markov chains).
• Strong track record of managing and growing high-performing data science teams.
• Excellent stakeholder management and communication skills – able to explain complex concepts in accessible language.
• Proficiency in tools such as Azure ML Studio , Databricks , AWS/SageMaker , Snowflake , and cloud-native platforms.
• Familiarity with CI/CD tools like Azure DevOps Pipelines or GitHub Actions .
• Comfortable working in Agile environments and contributing to iterative product development.

Bonus if you have:

• Experience integrating models into operational decision-making processes or logistics platforms.
• Exposure to Agile delivery methodologies or working in cross-functional squads.

What You’ll Get in Return

• A leadership role where your work has direct and measurable impact on operational efficiency and bottom-line performance.
• Dedicated support from MLOps and Engineering teams to accelerate delivery.
• Access to career development support including coaching, mentoring, and leadership training .
• A competitive salary package including car allowance , bonus , and comprehensive benefits such as enhanced parental leave, pension scheme, and mental health support.
• The chance to join a forward-thinking group of businesses that are reshaping the automotive industry with technology and data at the core.

Ready to lead a high-performing team where operational data science meets real-world impact?

Apply today or reach out for a confidential discussion.