Data Science Manager - Operational Research

ZipRecruiter; England; Hybrid; GBP 80,000 - 110,000; Full time

Job summary

A leading UK automotive group is seeking a Data Science Manager in Operational Research & Optimisation. This role involves leading a team of data scientists in applying advanced modelling techniques to enhance supply chain efficiency and operational workflows. The successful candidate will enjoy a competitive salary, car allowance, and significant benefits while spearheading innovative projects that drive measurable business value.

Benefits

Car allowance

10% bonus

Career development support

Comprehensive benefits

Enhanced parental leave

Qualifications

• Proven experience building optimisation models using Python libraries.
• Hands-on expertise in combinatorial optimisation and scheduling algorithms.
• Strong track record of managing data science teams.

Responsibilities

• Lead and mentor a data science team focused on operational optimisation.
• Define and deliver a product roadmap addressing operational challenges.
• Work cross-functionally to translate business requirements into solutions.

Skills

Optimisation models

Stakeholder management

Data science

Mathematical optimisation

Python

Agile methodologies

Tools

Azure ML Studio

Databricks

AWS/SageMaker

Snowflake

Azure DevOps Pipelines

Job description

Job Description

Data Science Manager - Operational Research & Optimisation

Location: Hybrid (1 day a week London)

Salary: £80,000-£110,000+ £6K Car Allowance + 10% Bonus + Excellent Benefits

We’re recruiting on behalf of one of the UK’s largest and most influential automotive groups for a Data Science Manager - Operational Research & Optimisation. 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 the 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, applying advanced mathematical optimisation techniques (e.g., Linear Programming, Scheduling, Graph Theory) to complex business problems, with the goal of improving 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.

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 .
• Proficiency in tools such as Azure ML Studio, Databricks, AWS/SageMaker, Snowflake, and cloud- 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.