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For Companies At a Glance
- Tasks: Lead a data science team to optimise operations and solve real-world challenges.
- Company: Join one of the UK's largest automotive technology groups driving innovation.
- Benefits: Enjoy a competitive salary, car allowance, bonus, and excellent benefits.
- Why this job: Make a measurable impact in a forward-thinking company reshaping the automotive industry.
- Qualifications: Experience in optimisation models, team leadership, and strong communication skills required.
- Other info: Hybrid work model with support from MLOps and Engineering teams.
The predicted salary is between 80000 - 100000 £ per year.
Location: Hybrid (1–2 days/week in Reading or Central London)
Salary: £80,000-£100,000+ 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 (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.
The Role
- Lead a growing group of data scientists focused on solving real-world operational challenges.
- Design and deploy advanced models that improve supply chain efficiency, optimise vehicle movement, and enhance operational workflows across the organisation.
- Supported by a modern MLOps and Data Engineering function.
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
- 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.
Contact Detail:
KDR Talent Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Manager (London Area)
✨Tip Number 1
Familiarise yourself with the latest optimisation techniques and tools mentioned in the job description, such as Python libraries like PuLP and SciPy.optimize. Being able to discuss these in detail during your interview will show your expertise and passion for the role.
✨Tip Number 2
Prepare examples of how you've successfully led data science teams in the past. Highlight specific projects where you applied advanced modelling techniques to solve operational challenges, as this will demonstrate your leadership capabilities and relevant experience.
✨Tip Number 3
Brush up on your stakeholder management skills. Be ready to explain complex data science concepts in simple terms, as you'll need to communicate effectively with non-technical stakeholders. Practising this skill can set you apart from other candidates.
✨Tip Number 4
Research the company’s current operations and any recent innovations in the automotive technology sector. Showing that you understand their business and how data science can drive efficiency will make a strong impression during your discussions.
We think you need these skills to ace Data Science Manager (London Area)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science and team leadership. Emphasise your skills in optimisation techniques and any specific tools mentioned in the job description, such as Python libraries and cloud platforms.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for operational optimisation and your ability to lead a team. Use specific examples from your past experiences to demonstrate how you have successfully solved complex business problems using data science.
Showcase Technical Skills: In your application, clearly outline your technical expertise in areas like combinatorial optimisation and scheduling algorithms. Mention any relevant projects or achievements that illustrate your proficiency with the required tools and methodologies.
Prepare for Interviews: If selected for an interview, be ready to discuss your approach to leading a data science team and how you communicate technical insights to non-technical stakeholders. Prepare examples of how you've integrated models into decision-making processes in previous roles.
How to prepare for a job interview at KDR Talent Solutions
✨Showcase Your Technical Skills
Be prepared to discuss your experience with optimisation models and Python libraries like PuLP or SciPy.optimize. Bring examples of past projects where you've successfully applied these techniques to solve complex business problems.
✨Demonstrate Leadership Experience
Highlight your experience in managing and mentoring data science teams. Share specific instances where you led a team to achieve significant results, focusing on how you fostered collaboration and growth within the group.
✨Communicate Clearly with Stakeholders
Practice explaining technical concepts in simple terms. You may be asked to demonstrate how you would communicate model outcomes to non-technical stakeholders, so think of examples where you've done this effectively in the past.
✨Familiarise Yourself with Agile Methodologies
Since the role involves working in Agile environments, brush up on Agile principles and be ready to discuss how you've contributed to iterative product development. Mention any experience with CI/CD tools like Azure DevOps or GitHub Actions.
