At a Glance
- Tasks: Lead the design and deployment of cutting-edge ML models to drive growth at Raylo.
- Company: Join a rapidly scaling tech company transforming how technology is accessed.
- Benefits: Fast-track your career, exclusive device leases, stock options, and hybrid working.
- Other info: Diverse and inclusive workplace with excellent career progression opportunities.
- Why this job: Make a real impact with AI while shaping the future of data science.
- Qualifications: 7+ years in data science, strong technical skills, and a passion for collaboration.
The predicted salary is between 72000 - 88000 £ per year.
Why We Exist
The world is moving away from rigid ownership models in favour of more flexible, affordable access. Our mission is to transform how technology is bought, used and reused — creating better outcomes for customers, brands and the planet.
What We've Built
Raylo is the subscription infrastructure that enables leading electronics brands, including PlayStation, HP and Dyson, to move from one-off device sales to recurring subscription programmes that increase conversion, deepen loyalty and capture more lifetime value. Behind that sits an AI-powered operating system that executes and manages device subscriptions end to end: credit and fraud decisioning, lifecycle operations, and the financing engine that enables brands to run subscription programmes at scale.
Brands can unlock a powerful new growth engine with Raylo across embedded checkout. We combine proprietary technology and data with the orchestration of physical assets, operating across credit, fraud, pricing, logistics, refurbishment, resale and customer care. With AI improving every cycle, our moat deepens with scale.
At Raylo, AI is woven into how we work every day. Teams are replacing spreadsheets with bespoke tooling, and anyone can query our data layer in plain English and get a real answer in seconds. We give every team their own hackathon: a chance to step back, start with a blank sheet, and ask: if we were starting today, how would we do this? AI gives people back time, and we expect them to spend it on the things no model can replicate: conversations, trust, craft and team judgement.
We hire to a high bar. You'll work with people who push you, raise your game and expect you to do the same.
Our Core Values:
- Be deeply curious – We thrive on innovation through diverse approaches, views, and people.
- Walk in your customer's shoes – To build the best products and make the best decisions for the long term, we must figure out what our customers need, not just what they want.
What to Expect
We're looking for an ambitious Lead Data Scientist to join Raylo and lead our advanced model building. Raylo has built a strong data foundation over the past five years, with robust analytics and data engineering powering commercial decision-making across the business. In this role, you'll take that foundation to the next level by designing, building and deploying predictive models that directly influence some of the most important drivers of Raylo's growth - from credit risk and customer retention to personalised recommendations.
You'll become Raylo's technical and strategic leader on:
- The cutting edge of ML and AI model development, applying the very best of what's possible to Raylo's hardest problems.
- Collaborating with teams across the business, to identify high impact opportunities for machine learning and advanced analytics.
- Taking these projects end-to-end from idea through to production deployment and monitoring.
- Redesigning our model building, deployment and monitoring process using agentic architecture and leveraging the latest LLM models.
You'll transform what's possible for a data science team, shaping and growing Raylo's data science function as we rapidly scale over the next five years. Raylo is a rapidly scaling, profitable company with ambitious international plans, and data sits at the core of how we make decisions and build our products. As a Lead Data Scientist, your work will have a huge impact both on Raylo as it goes through transformative growth and how the data function at Raylo wins in the world of AI powered agentic infrastructure. It's a rare opportunity to build best-in-class models using cutting edge technology, while defining the strategic vision for a category-defining business.
What You'll Do
Reporting to the VP of Strategy & Analytics, you'll define and lead Raylo's data science function, deploying cutting edge AI and ML to solve Raylo's hardest problems. You'll own end-to-end design, build and deployment of production-grade machine learning models - from credit risk and churn prediction to recommendation systems. You'll partner closely with teams across product, engineering, risk, operations and commercial to identify high-impact opportunities for advanced modelling and take them from ideation through to action.
You'll combine deep technical expertise with strong communication skills, translating complex modelling approaches into clear commercial benefits. Starting as a hands-on technical leader, you'll own and shape the data science roadmap at Raylo, defining how AI is used to transform the practice of data science and build the function from the ground up. Your work will directly influence key outcomes for Raylo — from managing risk and improving customer retention to unlocking new growth opportunities as the business scales internationally.
You'll Succeed With:
- A proven track record with 7+ years of experience in data science and predictive modelling.
- A 2:1 or higher from a top university, preferably in a STEM or quantitative discipline.
- Using your technical skills to build state of the art ML models and deploy them in production.
- The desire to build, coach and motivate a broader function while continuing to deliver on high quality IC projects.
- Collaborating in a fast-paced environment across the business with diverse skill sets and personality types. You have great stakeholder management skills and love using your analytical skills to champion data-driven decision-making and educate others.
- Taking responsibility and ownership for the work the entire area - if you're not getting it done, then no one is.
Opportunities & Benefits:
- Fast-track your career – 40% of our employees progress every review cycle (bi-annually).
- Exclusive Raylo device lease for employees.
- Private Medical Insurance.
- Stock options for all employees.
- L&D budget to support the skills you value.
- Hybrid working model.
- 33 days off, your way – 25 days + 8 bank holidays with full flexibility to use on the days that mean the most to you.
- Enhanced maternity, paternity, adoption or shared parental leave, if you've been with us for 12 months.
As an FCA-regulated business, we conduct background checks (DBS and AML) on all successful candidates who are offered a position at Raylo during the onboarding process.
Diversity & Inclusion at Raylo: At Raylo, we celebrate diversity and are committed to creating an inclusive workplace where everyone can thrive.
Lead ML / Data Scientist in London employer: Raylo
Raylo is an exceptional employer that fosters a dynamic and inclusive work culture, particularly in our Belfast location. With a hybrid work model and a focus on employee growth, we provide opportunities for professional development while encouraging a collaborative environment where your contributions directly impact our success in the fintech space.
StudySmarter Expert Advice🤫
We think this is how you could land Lead ML / Data Scientist in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Raylo!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Lead ML / Data Scientist at Raylo.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Raylo.
✨Apply Directly through Our Website
When you find a suitable opening like Lead ML / Data Scientist at Raylo, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Lead ML / Data Scientist in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Raylo, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Raylo. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Raylo
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Raylo!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.