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For Companies At a Glance
- Tasks: Transform customer data into insights for smarter marketing and personalised experiences.
- Company: Leading automotive e-commerce firm driving digital transformation.
- Benefits: Flexible hybrid working, strong focus on diversity, and employee wellbeing.
- Why this job: Join a collaborative team and make a real impact in the automotive industry.
- Qualifications: 2-3 years as a Data Scientist with skills in Python, SQL, and marketing analytics.
- Other info: Exciting opportunity in a fast-paced environment with career growth potential.
The predicted salary is between 28800 - 48000 £ per year.
The Company
Our client is a leading automotive e-commerce and retail organisation, delivering innovative digital solutions that connect buyers and sellers across the vehicle marketplace. Operating at scale and powered by advanced data and technology, they help customers make smarter purchasing decisions while enabling seamless, personalised online experiences. Their established Data Science function plays a central role in shaping commercial strategy and customer engagement across multiple brands.
Join a forward-thinking business at the forefront of automotive digital transformation.
- Work with large, rich datasets that directly influence real customer journeys.
- Be part of a highly experienced and collaborative data science team.
- Hybrid working model offering flexibility and work-life balance.
- Strong commitment to diversity, inclusion, and employee wellbeing.
The Role
Our client is seeking a talented Data Scientist – Marketing & Personalisation to join their growing analytics team. In this role, you’ll transform customer behaviour data into actionable insights that drive smarter marketing campaigns and personalised digital experiences. You’ll be involved across the full machine learning lifecycle – from discovery and model development through to deployment and optimisation in production environments.
- Build and enhance machine learning models that support marketing attribution and personalisation.
- Analyse customer journeys to identify insights that improve campaign performance.
- Develop forecasting, segmentation, recommender systems, and econometric models.
- Collaborate closely with digital analytics, marketing, and engineering teams.
- Deploy scalable, production-ready solutions using modern MLOps best practices.
Your Experience
This role is ideal for a curious, collaborative, and impact-driven data scientist who enjoys solving real business problems. You’ll have a strong technical foundation combined with hands-on experience in digital marketing analytics and machine learning.
- 2–3+ years of experience as a Data Scientist within marketing or digital analytics.
- Strong technical skills in Python and SQL.
- Experience with MMM, MTA, forecasting, segmentation, or recommender systems.
- Solid knowledge of statistics, econometrics, and causal inference.
- Familiarity with cloud platforms such as AWS, Azure, GCP, or Databricks.
- Experience deploying models into production using CI/CD and MLOps practices.
- Understanding of the digital marketing ecosystem and customer journey analytics.
Preferred but not essential: experience with A/B testing, API development, and agile development practices.
Next Steps
This Data Scientist – Marketing & Personalisation role is in high demand and won’t be open for long. If you’re excited about using advanced analytics to shape customer experiences and drive real commercial impact, we’d love to hear from you. Please apply today or get in touch for more information.
Data Scientist employer: KDR Talent Solutions
Contact Detail:
KDR Talent Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to marketing analytics and machine learning. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in digital marketing analytics. Practice common interview questions and be ready to discuss how you've used data to drive business decisions.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always looking for passionate individuals who want to make an impact in the automotive e-commerce space.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Data Scientist – Marketing & Personalisation. Highlight your experience with machine learning, digital marketing analytics, and any relevant projects that showcase your skills in Python and SQL.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data science and how you can contribute to our client's mission. Share specific examples of how you've transformed data into actionable insights in previous roles.
Showcase Your Technical Skills: Don’t forget to mention your technical expertise! If you’ve worked with cloud platforms like AWS or GCP, or have experience in deploying models using CI/CD practices, make sure these stand out in your application.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and get you on our radar quickly!
How to prepare for a job interview at KDR Talent Solutions
✨Know Your Data
Make sure you brush up on your knowledge of data science concepts, especially those related to marketing analytics. Be prepared to discuss how you've used Python and SQL in past projects, and think about specific examples where your insights led to improved campaign performance.
✨Showcase Your Problem-Solving Skills
During the interview, highlight your experience with machine learning models and how you've tackled real business problems. Prepare to discuss the full machine learning lifecycle, from model development to deployment, and be ready to share any challenges you faced and how you overcame them.
✨Understand the Company’s Ecosystem
Familiarise yourself with the automotive e-commerce landscape and the company's role within it. Research their digital marketing strategies and think about how your skills can enhance their customer journey analytics. This will show your genuine interest in the company and its mission.
✨Prepare for Technical Questions
Expect technical questions that assess your understanding of statistics, econometrics, and causal inference. Brush up on your knowledge of forecasting, segmentation, and recommender systems, and be ready to explain these concepts clearly. Practising coding challenges in Python can also give you an edge.
