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- Tasks: Lead a team in developing machine learning models for pricing strategies.
- Company: Join a major UK automotive group focused on data-driven decision-making.
- Benefits: Enjoy a flexible hybrid work model and support for skill development.
- Why this job: Make a real impact on pricing and profitability in a fast-paced environment.
- Qualifications: Experience in pricing analytics and managing data science teams is essential.
- Other info: Collaborate with MLOps and engineering teams to drive innovation.
The predicted salary is between 72000 - 98000 £ per year.
Location: Hybrid (1–2 days/week in London)
Are you an experienced Data Science Manager with a passion for pricing strategy, machine learning, and commercial impact? We're hiring on behalf of a major UK-based automotive group seeking a Data Science Manager to lead pricing analytics and shape the future of their data products. This is a high-profile opportunity to head up a dedicated Valuations & Pricing team, delivering cutting-edge machine learning solutions that influence decision-making across a large, fast-moving business. You'll have access to vast datasets, modern tooling, and the support of experienced MLOps and Data Engineering teams – freeing you to focus on model innovation, business impact, and team leadership.
Key Responsibilities- Lead and coach a team of data scientists focused on pricing and valuation products.
- Develop and deploy machine learning models that drive pricing accuracy and business performance.
- Own the pricing analytics roadmap, aligning with senior stakeholders to prioritise and deliver key initiatives.
- Work cross-functionally with Marketing and Operations data teams to extend the reach of data science across the organisation.
- Collaborate with MLOps and Engineering teams to ensure seamless product delivery and integration.
- Promote the use and value of pricing models to non-technical stakeholders through clear and effective communication.
- Continuously improve the product lifecycle, model pipelines, and development processes to enable rapid innovation.
- Proven track record in pricing analytics, valuation modelling, or similar domains.
- Strong hands-on experience developing ML solutions in Python.
- Experience managing and growing high-performing data science teams.
- Ability to build and communicate complex solutions to stakeholders across different levels and disciplines.
- Proficiency working with modern cloud-based tools (e.g., Azure ML, Databricks, Snowflake, SageMaker, etc.).
- Deep knowledge of machine learning techniques including predictive modelling, pattern recognition, and optimisation.
- Strong stakeholder management and product ownership skills.
- Experience with CI/CD tools such as Azure DevOps Pipelines or GitHub Actions.
- Exposure to Marketing Data Science (e.g., Marketing Mix Modelling, Multi-Touch Attribution) or Operational Research.
- Experience working in an Agile development environment.
- The chance to lead a strategically critical function with high visibility across the organisation.
- Dedicated time and support to grow your skills as a people manager and strategic leader.
- A flexible hybrid work model (Reading or London) and a collaborative environment.
- A role where your models directly shape pricing, influence profitability, and deliver real commercial outcomes.
- Support from seasoned MLOps and engineering teams – letting you focus on research, modelling, and innovation.
If you’re passionate about pricing science and ready to step into a leadership role where your work has real business impact, we’d love to hear from you. Apply now or get in touch for a confidential discussion.
Seniority level: Mid-Senior level
Employment type: Full-time
Job function: Information Technology
Industries: Data Infrastructure and Analytics, Information Services, and IT Services and IT Consulting
Data Science Manager employer: KDR Talent Solutions
Contact Detail:
KDR Talent Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Manager
✨Tip Number 1
Familiarise yourself with the latest trends in pricing analytics and machine learning. Being able to discuss recent advancements or case studies during your conversations can demonstrate your passion and expertise in the field.
✨Tip Number 2
Network with professionals in the automotive industry or data science community. Attend relevant meetups or webinars to connect with potential colleagues or mentors who can provide insights into the company culture and expectations.
✨Tip Number 3
Prepare to showcase your leadership skills by thinking of examples where you've successfully managed teams or projects. Highlighting your ability to coach and develop others will be crucial in demonstrating your fit for a managerial role.
✨Tip Number 4
Brush up on your communication skills, especially when it comes to explaining complex data science concepts to non-technical stakeholders. Practising how to convey your ideas clearly can set you apart in interviews.
We think you need these skills to ace Data Science Manager
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in pricing analytics and machine learning. Use specific examples of projects you've led or contributed to, especially those that demonstrate your ability to drive business performance.
Craft a Compelling Cover Letter: In your cover letter, express your passion for pricing strategy and data science. Mention how your leadership experience aligns with the role and how you can contribute to the company's goals. Be sure to address the key responsibilities outlined in the job description.
Showcase Technical Skills: Clearly outline your technical skills relevant to the position, such as proficiency in Python, experience with cloud-based tools, and familiarity with CI/CD processes. Providing concrete examples of how you've used these skills in past roles will strengthen your application.
Highlight Stakeholder Management Experience: Since the role involves working with various stakeholders, emphasise your experience in managing relationships and communicating complex solutions effectively. Include examples of how you've successfully collaborated across teams to achieve common goals.
How to prepare for a job interview at KDR Talent Solutions
✨Showcase Your Leadership Skills
As a Data Science Manager, you'll be leading a team. Be prepared to discuss your experience in managing and growing high-performing teams. Share specific examples of how you've coached team members and fostered a collaborative environment.
✨Demonstrate Technical Proficiency
Make sure to highlight your hands-on experience with machine learning solutions, particularly in Python. Be ready to discuss the tools you’ve used, such as Azure ML or Databricks, and how they contributed to successful projects.
✨Communicate Complex Ideas Simply
You'll need to promote pricing models to non-technical stakeholders. Practice explaining complex concepts in a straightforward manner, using relatable examples to ensure clarity and understanding.
✨Align with Business Goals
Understand the company's pricing strategy and how data science can enhance it. Be prepared to discuss how your previous work has directly influenced business outcomes and how you plan to align your team's efforts with the organisation's objectives.
