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 experience and data science.
- Benefits: Competitive salary, bonus, hybrid work, and fast track to management.
- Other info: Join a newly scaling team with strong investment and growth opportunities.
- Why this job: Shape the future of customer analytics and GenAI in real-world applications.
- Qualifications: Strong Python, machine learning, and SQL skills; consulting experience is a plus.
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 Customer Data Scientist in London employer: Xpand Group
Join a leading global consulting firm that is at the forefront of customer data science innovation in London. With a strong focus on employee growth, you will have the opportunity to shape advanced analytics practices while enjoying a collaborative and dynamic work culture. Benefit from competitive compensation, a hybrid working model, and the chance to work on impactful projects that enhance customer engagement for major brands.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Customer Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend events, and connect on LinkedIn. We can’t stress enough how important it is to build relationships; you never know who might have the inside scoop on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those related to customer analytics. We recommend sharing this on platforms like GitHub or even your own website to catch the eye of potential employers.
✨Tip Number 3
Prepare for interviews by practising common questions and case studies relevant to customer data science. We suggest doing mock interviews with friends or using online resources to get comfortable with the format and expectations.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications that way!
We think you need these skills to ace Senior Customer Data Scientist 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 consulting approach. Be sure to mention any exposure to GenAI or LLM applications, as this will catch our eye.
Showcase Your Problem-Solving Skills:In your application, give examples of how you've tackled complex problems in previous roles. We love candidates who can translate data insights into actionable commercial recommendations, so share specific instances where you’ve made an impact!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Xpand Group
✨Know Your Data Science Stuff
Make sure you're up to speed with Python and machine learning techniques. Brush up on your predictive modelling skills, especially classification and regression, as you'll need to demonstrate your hands-on experience during the interview.
✨Understand the Client's Needs
Research the company and its clients thoroughly. Be ready to discuss how you can apply customer behaviour analysis and segmentation to improve their commercial performance. Show them you can translate data insights into actionable recommendations.
✨Showcase Your Consulting Skills
Even if you don't have extensive consulting experience, highlight any relevant projects where you've worked closely with stakeholders. Emphasise your communication skills and how you've successfully collaborated to solve problems in a client-facing environment.
✨Get Familiar with GenAI Applications
Since this role involves applied GenAI, make sure you understand its use cases in customer and marketing contexts. Be prepared to discuss any experience you have with LLM-based applications and how they can enhance customer engagement and marketing effectiveness.
