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.
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 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 part of a dynamic team that leverages cutting-edge data science and AI to drive impactful solutions for major consumer brands.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Customer Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend events, 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 bring to the table.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios specific to customer data science. Think about how you can demonstrate your problem-solving skills and technical expertise in real-world situations.
✨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
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Senior Customer Data Scientist role. Highlight your hands-on Python and machine learning experience, as well as any relevant consulting or customer analytics work you've done.
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 you can contribute to our team. Mention specific projects or experiences that relate to customer behaviour analysis or predictive modelling.
Showcase Your Technical Skills:Don’t forget to emphasise your technical abilities, especially in Python, SQL, and any GenAI applications you've worked with. We want to see how you can apply these skills to real-world client challenges, so be specific!
Apply Through Our Website:We encourage you to apply directly through our website. 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 Salt
✨Know Your Data Science Stuff
Make sure you brush up on your Python and machine learning skills. Be ready to discuss specific projects where you've built and deployed predictive models. They’ll want to see how you can apply your technical knowledge to real-world problems, so have some examples up your sleeve.
✨Understand the Client's Needs
Research the company and its clients before the interview. Understand their business model and how customer analytics can drive their success. This will help you tailor your answers and show that you can translate data insights into actionable commercial recommendations.
✨Show Off Your Communication Skills
Since this role involves a lot of client interaction, practice explaining complex data concepts in simple terms. Think about how you can convey your findings to stakeholders who may not have a technical background. Clear communication is key!
✨Get Familiar with GenAI Applications
Since they’re looking for someone with exposure to GenAI and LLM-based applications, make sure you understand how these technologies can be applied in customer and marketing contexts. Be prepared to discuss any relevant experience or ideas you have for using GenAI in their projects.
