Data Science Manager
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Data Science Manager
Job Details
Published:
07-06-2025
Salary:
Location:
London
Category:
Permanent
Sector:
Analytics
Reference:
4724
Work Model:
Hybrid
Description
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.