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- Tasks: Lead a team of data scientists to solve operational challenges using advanced optimisation techniques.
- Company: Join one of the UK's largest automotive groups, driving innovation in the industry.
- Benefits: Enjoy a competitive salary, car allowance, bonus, and excellent benefits including mental health support.
- Why this job: Make a real impact on operational efficiency while working with cutting-edge technology and data.
- Qualifications: Experience in building optimisation models and managing high-performing data science teams is essential.
- Other info: Hybrid work model with one day a week in Reading or Central London.
The predicted salary is between 80000 - 110000 £ per year.
Location: Hybrid (1 day a week in Reading or Central 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 Lead Data Scientist. 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:
- 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.
Lead Data Scientist employer: KDR Talent Solutions
Contact Detail:
KDR Talent Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist
✨Tip Number 1
Familiarise yourself with the specific optimisation techniques mentioned in the job description, such as Linear Programming and Graph Theory. Being able to discuss these concepts confidently during your interview will demonstrate your expertise and passion for the role.
✨Tip Number 2
Showcase your leadership skills by preparing examples of how you've successfully managed and grown data science teams in the past. Highlighting your experience in mentoring others will resonate well with the hiring managers looking for a strong team leader.
✨Tip Number 3
Research the company’s current operational challenges and think about how your skills can address them. Being able to present tailored solutions or ideas during your discussions will set you apart from other candidates.
✨Tip Number 4
Prepare to discuss your experience with cloud platforms and CI/CD tools, as these are crucial for the role. Being able to articulate how you've used these technologies in previous projects will show that you're ready to hit the ground running.
We think you need these skills to ace Lead Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with optimisation models and data science leadership. Use specific examples that demonstrate your expertise in Python libraries and advanced mathematical techniques relevant to the role.
Craft a Compelling Cover Letter: In your cover letter, express your passion for operational optimisation and how your background aligns with the company's goals. Mention your experience in leading teams and delivering measurable business value through data science.
Showcase Relevant Projects: Include details of specific projects where you applied optimisation techniques or led a data science team. Highlight the impact these projects had on operational efficiency or decision-making processes.
Prepare for Technical Questions: Be ready to discuss your technical skills in detail, especially around combinatorial optimisation and scheduling algorithms. Prepare to explain complex concepts in simple terms, as you'll need to communicate effectively with non-technical stakeholders.
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 applied advanced mathematical techniques to solve complex problems.
✨Demonstrate Leadership Experience
Highlight your experience in managing and mentoring data science teams. Share specific instances where you successfully led a team to achieve operational goals, focusing on how you fostered collaboration and innovation.
✨Communicate Clearly with Stakeholders
Practice explaining complex technical concepts in simple terms. During the interview, be ready to demonstrate how you would communicate insights to non-technical stakeholders, ensuring they understand the value of your work.
✨Familiarise Yourself with Agile Methodologies
Since the role involves working in Agile environments, brush up on Agile principles and practices. Be ready to discuss how you've contributed to iterative product development and how you can apply these methodologies in your new role.
