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 opportunities for rapid career advancement.
- Other info: Join a newly scaling team with significant investment and growth potential.
- Why this job: Shape the future of customer analytics and apply GenAI in real-world scenarios.
- Qualifications: Strong Python and machine learning skills, with experience in customer data analysis.
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 Slough employer: Salt
As a leading global consulting firm, we offer an exceptional work environment that fosters innovation and collaboration in the heart of London. 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 capability. Join us to be at the forefront of applying advanced analytics and GenAI in real-world scenarios, all while enjoying competitive compensation and a supportive team culture.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Customer Data Scientist in Slough
✨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 data science projects, especially those related to customer analytics. 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 customer data science. Be ready to discuss how you've used Python and machine learning to solve real-world problems.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Customer Data Scientist in Slough
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Customer Data Scientist role. 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 exposure to GenAI or LLM applications.
Showcase Your Problem-Solving Skills:In your application, emphasise your ability to translate data insights into commercial recommendations. We love candidates who can combine technical skills with commercial problem-solving, so share examples of how you've done this in past roles.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to upload your tailored CV and cover letter directly. Plus, it shows us you’re serious about joining 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 the Client's Needs
Research the company and its clients thoroughly. Understand their business model and how customer analytics can drive their success. This will help you translate data insights into commercial recommendations during the interview.
✨Showcase Your Communication Skills
Since this role involves a lot of client-facing work, practice explaining complex data concepts in simple terms. Prepare examples of how you've effectively communicated insights to stakeholders in the past.
✨Get Familiar with GenAI Applications
As the role involves applied GenAI use cases, make sure you know the latest trends and applications in this area. Be prepared to discuss any relevant experience you have with LLMs or similar technologies.
