At a Glance
- Tasks: Design and build cutting-edge recommender systems for efficient parcel delivery.
- Company: Join Relay, a fast-growing logistics startup reshaping e-commerce.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Dynamic team environment focused on collaboration and continuous improvement.
- Why this job: Make a real impact in logistics with innovative technology and data-driven solutions.
- Qualifications: Experience in building scalable recommender systems and strong analytical skills.
The predicted salary is between 63000 - 77000 £ per year.
Relay is fundamentally reshaping how goods move in an online era. Backed by Europe’s largest-ever logistics Series A ($35M) led by deep-tech investors Plural, and a recently closed Series B ($95M), Relay is scaling faster than 99% of venture-backed startups. We're assembling the most talent-dense team the logistics industry has ever seen.
Relay’s Mission is to free commerce from friction. Today, high delivery costs act as a hidden tax on e-commerce, quietly shaping what can be sold online and limiting who can participate. We envision a world where more goods move more freely between more people, making the online shopping experience seamless and accessible to everyone.
THE TEAM
- ~160 people, around half in engineering, product and data
- 45+ advanced degrees across computer science, mathematics and operations research
- Thousands of data points captured, calculated, analysed and predicted for every single parcel we handle
- An intellectually vibrant culture of first‑principles thinking, tight feedback loops and relentless experimentation
Every courier who works with Relay chooses their day. A day is a set of routes that have to fit together, and every courier's ideal day competes with everyone else's. Work is finite and every route still has to be covered, so matching thousands of couriers to the work they want is a recommendation problem with few precedents.
Science at Relay is the brain of the operation: machine learning, operational research, recommender systems, causal inference, location intelligence and experimentation, working together to decide how every parcel gets delivered. There's no existing recommender to iterate on. You'll build it.
Recommender Systems Highlights
- Combinatorial, constrained and competitive: every recommendation has to be feasible for the whole network, not just right for one courier.
- Your models power large-scale optimisation that balances thousands of couriers' preferences against the constraints of a physical network.
- Price is part of the recommendation, so economics, personalisation and optimisation have to work as one.
- Our apps collect millions of data points every day.
The Opportunity
As an Applied Scientist at Relay, you'll:
- Set the standard for recommender systems at Relay.
- Lead the evolution of Relay's recommender from research to production.
- Design and build the recommender systems that power Relay's key decisions.
- Partner with Operational Research to unite recommender models and optimisation.
- Contribute to Relay's research culture, and develop our voice in the tech community.
We're looking for candidates who…
- Have built recommender systems at scale, owned them in production, and led their direction.
- Bring deep expertise in recommender systems, reinforcement learning and LLMs, whether from a PhD, publications, or years at the frontier in industry.
- Think in experiments, and let evidence guide decisions.
- Are energised by open-ended problems, and know how to make them tractable.
- Collaborate generously, and explain complex ideas simply.
Don't tick every box? If this problem excites you, we'd still love to hear from you.
Who Thrives at Relay?
- Aim with Precision: You define problems clearly and measure your impact meticulously.
- Play to Win: You chase bold bets, tackle the hard stuff, and view constraints as fuel, not friction.
- 1% Better Every Day: You believe that small, consistent improvements lead to exponential growth. You move quickly, deliver results, and learn from every experience.
- All In, All the Time: You show up and step up. You take ownership from start to finish and do what it takes to deliver when it counts.
- People-Powered Greatness: You invest in your teammates. You give and receive feedback with care and candour. You build trust through high standards and shared success.
- Grow the Whole Pie: You seek out win‑win solutions for merchants, couriers, and our customers, because when they thrive, so do we.
Relay is an equal‑opportunity employer committed to diversity, inclusion, and fostering a workplace where everyone thrives.
Applied Scientist, Ranking & Recommendations employer: Relay
Relay is an exceptional employer, offering a dynamic work environment at our London Sort Centre where innovation meets operational excellence. With a strong focus on employee growth and development, we foster a culture of collaboration and continuous improvement, ensuring that every team member has the opportunity to contribute to our mission of transforming logistics. Our commitment to diversity and inclusion, combined with competitive benefits and a fast-paced, intellectually stimulating atmosphere, makes Relay a truly rewarding place to work.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Scientist, Ranking & Recommendations
✨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 Relay!
✨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 Applied Scientist, Ranking & Recommendations at Relay.
✨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 Relay.
✨Apply Directly through Our Website
When you find a suitable opening like Applied Scientist, Ranking & Recommendations at Relay, 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 Applied Scientist, Ranking & Recommendations
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 Relay, 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 Relay. 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 Relay
✨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 Relay!
✨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.
