At a Glance
- Tasks: Lead a data science team to create innovative pricing and personalisation models.
- Company: Join a well-known consumer brand with a focus on digital loyalty.
- Benefits: Competitive salary, hybrid work, and a completion bonus up to 20%.
- Other info: 11-month contract with excellent career growth opportunities.
- Why this job: Shape the future of pricing and customer experiences in a high-profile role.
- Qualifications: Experience in revenue management, machine learning, and leading data science projects.
The predicted salary is between 95000 - 105000 £ per year.
An established, consumer‑facing brand is hiring a Lead Data Scientist for an 11‑month maternity cover. This is a rare chance to shape the future of pricing, revenue optimisation and personalisation across a high‑profile digital loyalty and rewards business.
The opportunity
- You’ll lead a small, ambitious data science team, owning the design and delivery of machine learning and optimisation models that drive dynamic pricing, customer intelligence and personalised experiences.
- You will be the day‑to‑day technical authority, partnering closely with Product, Revenue Management, Pricing and Engineering to take models from idea to production and measure real‑world impact.
What you’ll do
- Lead the design, development and deployment of ML and AI‑powered data products for pricing and revenue.
- Act as technical lead across modelling work, championing rigour, robustness and reliability.
- Guide customer intelligence and personalisation models, including recommender systems.
- Work with Product, Delivery and ML Engineering to productionise models and monitor performance.
- Mentor and support data scientists, fostering curiosity, learning and technical excellence.
- Promote a data‑driven culture through experimentation, storytelling and clear communication.
What you’ll bring
- Proven experience implementing or optimising revenue management systems and pricing strategies.
- Strong background in optimisation and machine learning (time‑series forecasting, regression, mathematical optimisation).
- Experience leading or managing data scientists on impactful ML / optimisation projects.
- Excellent Python and SQL skills, with clean, maintainable code.
- Practical MLOps experience (deployment, monitoring, lifecycle management) in a cloud environment (AWS or similar).
- Comfortable working with large, imperfect datasets and making sound, pragmatic decisions.
- Familiarity with recommender systems, personalisation or generative AI is a plus.
Contract & package
- 11‑month fixed‑term contract (maternity cover).
- Hybrid working – typically 1 day per week in the London office.
- £95,000‑£105,000 per annum, plus up to 20% completion bonus.
- Target start date: January 2026.
- Rates depend on experience and client requirements.
Lead Data Scientist employer: Salt Digital Recruitment
Join a leading consumer-facing brand as a Lead Data Scientist in London, where you will have the unique opportunity to shape pricing and personalisation strategies within a high-profile digital loyalty business. Our hybrid work culture promotes flexibility and collaboration, while our commitment to employee growth ensures you will thrive through mentorship and continuous learning. With competitive compensation and a dynamic team environment, this role offers a meaningful chance to make a real impact in the world of data science.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, especially those who work in pricing and personalisation. A friendly chat can lead to insider info about job openings or even a referral.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your best machine learning and optimisation projects. When you get the chance to chat with potential employers, share how you've tackled real-world problems with your expertise.
✨Tip Number 3
Be ready for technical interviews! Brush up on your Python and SQL skills, and be prepared to discuss your experience with MLOps and cloud environments. Practising common data science interview questions can give you the edge you need.
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight your experience in revenue management and personalisation, and let us know why you're excited about this role.
We think you need these skills to ace Lead Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Lead Data Scientist. Highlight your experience with machine learning, optimisation, and any relevant projects that showcase your skills in pricing and personalisation.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've led data science teams or implemented successful pricing strategies in the past.
Showcase Your Technical Skills:Don’t forget to mention your Python and SQL expertise! We want to see how you’ve used these skills in real-world scenarios, especially in deploying models and working with large datasets.
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 keep track of your application and ensure it gets the attention it deserves!
How to prepare for a job interview at Salt Digital Recruitment
✨Know Your Stuff
Make sure you brush up on your machine learning and optimisation knowledge. Be ready to discuss specific models you've worked on, especially in pricing and personalisation. This is your chance to showcase your technical expertise and how it can benefit the company.
✨Showcase Leadership Skills
As a Lead Data Scientist, you'll be guiding a team. Prepare examples of how you've mentored others or led projects in the past. Highlight your ability to foster a data-driven culture and how you’ve encouraged curiosity and learning within your teams.
✨Communicate Clearly
Practice explaining complex concepts in simple terms. You’ll need to partner with various teams, so being able to communicate your ideas clearly is crucial. Think about how you can tell a compelling story around your data projects and their impact.
✨Prepare for Practical Scenarios
Expect to tackle real-world problems during the interview. Brush up on your practical MLOps experience and be ready to discuss how you would approach deploying and monitoring models in a cloud environment. This will demonstrate your hands-on skills and readiness for the role.
