At a Glance
- Tasks: Deliver hands-on data science and customer analytics for consumer-focused projects.
- Company: Global consulting firm with a focus on customer data science and AI.
- Benefits: Competitive salary, bonus, hybrid work, and fast track to management.
- Other info: Dynamic role with opportunities for growth in a newly scaling capability.
- Why this job: Shape the future of customer analytics and make a real impact in client environments.
- Qualifications: Strong Python and machine learning skills; experience with customer data.
The predicted salary is between 60000 - 70000 € per year.
A global consulting firm is building a new London-based Customer Data Science capability within its broader customer, digital, and marketing practice. The team focuses on combining customer experience, data science, and applied AI to help large consumer-facing organisations improve commercial performance, customer engagement, and marketing effectiveness. This is a newly scaling capability with strong investment and the opportunity to shape how advanced customer analytics and GenAI are applied in real-world client environments.
You will deliver hands-on data science and customer analytics work across a range of consumer-focused client projects. This is a delivery-heavy role combining technical data science with commercial problem solving and client-facing consulting, with a fast track to Management.
Typical work includes:
- Customer behaviour analysis and segmentation
- Marketing and CRM performance analytics
- Loyalty and retention modelling
- Web, product, and digital analytics
- Predictive modelling and forecasting
- Applied GenAI / LLM use cases in customer and marketing contexts
- Personalisation and optimisation initiatives
Requirements
- Strong hands-on Python and machine learning experience
- Ability to build and deploy predictive models (classification, regression, clustering, forecasting)
- Experience working with customer, CRM, marketing, or digital behavioural data
- Exposure to GenAI / LLM-based applications (build, evaluate, or implement use cases)
- SQL proficiency
- Strong stakeholder communication skills
- Ability to translate data insights into commercial recommendations
- Experience in a consulting, agency, or in-house analytics environment
- Consulting experience is beneficial but not essential. Strong candidates from consumer-facing or agency backgrounds are welcome.
Senior Data Scientist (Customer) in London employer: Salt
As a leading global consulting firm, we offer an exceptional work environment in London that fosters innovation and collaboration. Our hybrid work model promotes a healthy work-life balance while providing ample opportunities for professional growth and development within our newly established Customer Data Science team. Join us to be at the forefront of applying advanced analytics and AI in real-world scenarios, all while enjoying competitive compensation and a supportive culture that values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist (Customer) in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those related to customer analytics. We want to see how you’ve tackled real-world problems, so make sure to highlight your hands-on experience with Python and machine learning.
✨Tip Number 3
Prepare for interviews by practising common data science scenarios. We recommend running through case studies that involve customer behaviour analysis or predictive modelling. This will help you demonstrate your problem-solving skills and technical expertise.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals who can contribute to our Customer Data Science capability. Your next big opportunity could be just a click away!
We think you need these skills to ace Senior Data Scientist (Customer) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Senior Customer Data Scientist. Highlight your hands-on Python and machine learning experience, and don’t forget to showcase any relevant projects that demonstrate your skills in customer behaviour analysis and predictive modelling.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about data science and how your experience aligns with our focus on customer engagement and marketing effectiveness. Be sure to mention any specific projects or achievements that relate to the job description.
Showcase Your Problem-Solving Skills:In both your CV and cover letter, make sure to highlight examples where you've tackled complex problems using data science. We love seeing how you’ve translated data insights into actionable recommendations, especially in a consulting context!
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 ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Salt
✨Know Your Data Science Stuff
Make sure you brush up on your Python and machine learning skills before the interview. Be ready to discuss specific projects where you've built and deployed predictive models, as this role is all about hands-on data science work.
✨Understand Customer Analytics
Familiarise yourself with customer behaviour analysis and segmentation techniques. Be prepared to share examples of how you've used data to drive marketing performance or improve customer engagement in previous roles.
✨Showcase Your Communication Skills
Since this role involves client-facing consulting, practice explaining complex data insights in simple terms. Think of ways to demonstrate how you've translated data findings into actionable commercial recommendations in past experiences.
✨Get Acquainted with GenAI
As the role involves applied GenAI use cases, do some research on how GenAI and LLMs can be leveraged in customer and marketing contexts. Be ready to discuss any relevant experience or ideas you have for implementing these technologies.
