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Senior Data Scientist - Operational Research (Routing)

Company mission

In the future, almost everything we consume will simply materialise on our doorsteps – what we call “e-commerce” today will simply be “commerce” tomorrow. But if we continue on today’s trajectory, the growth of e-commerce risks damaging the environment, alienating our communities, and straining the bottom-line for small businesses.

Relay is an e-commerce-native logistics network. We are built from the ground up for environmental, social, and economic sustainability. By building from the ground up we are able to entirely rethink both the middle and last mile enabling us to reduce the number of miles driven to deliver each parcel, lower carbon emissions, and lower costs, all while channelling funds to community members.

At the same time, we’re fixing the last broken aspect of e-commerce for consumers: delivery. As shoppers, we should have complete control over when and how we receive our purchases, and we should be able to return unwanted items as easily as we ordered them. That’s why whenever you buy from a merchant powered by Relay, you’ll be able to reschedule your delivery at any time. And if you don’t like what you ordered, at the tap of a button we’ll send someone to pick it up.

To orchestrate this complex ballet, Relay relies on a wide range of technologies, from advanced routing and planning to sophisticated user experiences that guide our team members on the ground. 

About the role

As a highly operational business, we rely on data science to guide how every parcel moves through our network — from when it enters the system to when it’s delivered at the doorstep.

We’re hiring a Senior Data Scientist to help us design, test, and improve the algorithms that power routing across Relay’s first, middle, and last mile. This role sits at the intersection of operations research and applied data science; it’s well-suited to someone who enjoys turning real-world routing challenges into scalable, production-ready solutions.

You’ll work directly in a cross-functional squad which includes Operations, Engineering, Data Analytics, and other Data Scientists, to improve how parcels are grouped, sequenced, and routed across the network. You’ll also play a key role in shaping our future routing strategy, helping us unlock efficiency, scale into new service areas, and adapt to new commercial requirements. 

It’s a hands-on, high-impact role with strong exposure to both technical architecture and network operations.

What you’ll do

  • Design, prototype, and iterate on routing algorithms across first, middle, and last mile

  • Build simulation and optimisation tools that help us test new strategies and operational flows

  • Work directly with data analysts to benchmark routing performance and quantify gains from proposed improvements

  • Collaborate with engineers and operations leads to embed models into planning and execution

  • Translate operational and commercial constraints into tractable optimisation problems

  • Work with MLEs and Staff Data Scientists to productionise models and build scalable optimisation pipelines

  • Bring a scientific lens to operational design; measure rigorously, test thoughtfully

What we’re looking for

  • 6+ years of experience in data science, with deep expertise in modelling, experimentation, and statistical analysis

  • Strong foundations in operations research; experience with mixed integer programming, solvers, optimisation libraries, or related approaches 

  • Deep experience with Python and SQL

  • Well-developed analytical and problem-solving skills, with a proven ability to move from ambiguity to structure

  • Effective communication skills — you can explain technical results clearly to non-technical audiences

  • Comfortable working across functions and disciplines to drive impact

Nice to haves

  • Experience working on routing, scheduling, or network optimisation problems 

  • Experience in fast-scaling startups or operational teams

  • Experience in logistics, mobility, marketplaces, or other operationally complex businesses

What we offer

  • 25 days annual leave per year (plus bank holidays).

  • Equity package.

  • Bupa Global: Business Premier Health Plan - Comprehensive global health insurance with direct access to specialists, dental care, mental health support and more.

  • Contributory pension scheme.

  • Hybrid working

  • Free membership of the gym in our co-working space in London.

  • Cycle-to-work scheme

  • A culture of learning and growth, where you're encouraged to take ownership from day one.

  • Plenty of team socials and events - from pottery painting to life-size Monopoly and escape rooms

Average salary estimate

$90000 / YEARLY (est.)
min
max
$80000K
$100000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Data Scientist - Operational Research (Routing), Relay Technologies

We are excited to welcome a Senior Data Scientist specializing in Operational Research (Routing) to Relay in London! At Relay, we're on a mission to redefine the e-commerce logistics landscape, emphasizing sustainability while ensuring a seamless experience for shoppers. In this role, you will play a crucial part in analyzing and optimizing how each parcel traverses our comprehensive logistics network. As a Senior Data Scientist, your expertise will enable us to design, test, and refine the algorithms that power routing for first, middle, and last-mile delivery. Collaborating closely with Operations, Engineering, and other Data Scientists, you will be integral to improving parcel grouping, sequencing, and routing. We're looking for someone with at least 6 years in data science and a solid grip on operations research, along with a strong command of Python and SQL. You'll have the opportunity to build simulation and optimization tools, work on innovative routing algorithms, and transform complex operational requirements into solvable optimization challenges. This role is not just about crunching numbers; it’s about translating data into impactful strategies that enhance our delivery network and customer satisfaction. Plus, you’ll be part of a hands-on, dynamic squad with a culture that fosters growth and creativity. If you’re ready to take on a high-impact role that combines your analytical talent with a passion for sustainability, Relay is the place for you!

Frequently Asked Questions (FAQs) for Senior Data Scientist - Operational Research (Routing) Role at Relay Technologies
What are the primary responsibilities of a Senior Data Scientist at Relay?

As a Senior Data Scientist at Relay, your main responsibilities include designing and optimizing routing algorithms, building simulation and optimization tools, collaborating with cross-functional teams to benchmark routing performance, and translating operational constraints into optimization problems. Your work will directly influence how parcels are managed through our network.

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What qualifications are necessary to apply for the Senior Data Scientist position at Relay?

To qualify for the Senior Data Scientist role at Relay, candidates should have 6+ years of experience in data science, with a strong foundation in operations research, modeling, and statistical analysis. Proficiency in Python and SQL is crucial, along with effective communication skills to share technical insights with various audiences.

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What programming languages and tools will I need to know for the Senior Data Scientist role at Relay?

For the Senior Data Scientist position at Relay, candidates should have deep expertise in Python and SQL. Familiarity with optimization libraries and tools related to mixed integer programming and operations research will also be significant assets.

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How does Relay foster collaboration among team members for the Senior Data Scientist position?

At Relay, collaboration is key! As a Senior Data Scientist, you will work alongside engineers, operations leads, data analysts, and fellow data scientists. This interdisciplinary team approach ensures your insights and models are effectively implemented and tested across the logistics network.

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What type of work environment can I expect as a Senior Data Scientist at Relay?

Relay offers a dynamic and innovative work environment where team members are encouraged to take ownership from day one. You can expect collaborative workspaces, hybrid scheduling options, and a culture focused on learning and growth, making it an exciting place to bring your data science expertise.

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Common Interview Questions for Senior Data Scientist - Operational Research (Routing)
Can you describe a past project where you developed a routing algorithm?

In answering this question, detail a specific project where you utilized routing algorithms. Explain the objective, your approach to data analysis, the technologies or methodologies used, and the outcome. Highlight how your work contributed to overall project success.

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How do you ensure your algorithms are efficient and scalable?

To address this, discuss your approach to algorithm optimization, including techniques like benchmarking performance, and utilizing simulation tools to test scalability under varying conditions. Explain how you balance complexity and performance.

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How would you handle conflicts in data between various departments?

Articulate your strategy for addressing differing perspectives by focusing on data-driven decision-making. Emphasize your willingness to collaborate, clarify any discrepancies through discussions, and advocate for a solutions-oriented approach.

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What methods do you use to translate technical concepts for non-technical teammates?

Emphasize the importance of clarity and simplicity. Describe how you break down complex concepts into layman's terms using visuals, real-world analogies, and examples, ensuring everyone understands the implications of your work.

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Could you explain a time when you had to adapt quickly to new information?

Provide a specific example where the data or operational requirements changed unexpectedly, how you assessed the situation, and the steps you took to adjust your project strategy or algorithms accordingly.

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What is your experience with cross-functional teamwork in data science projects?

Share experiences where collaboration played a vital role in project outcomes. Discuss how you communicated with different team members, what you learned from those collaborations, and any tools or methods you used to facilitate teamwork.

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Describe how you approach benchmarking routing performance metrics.

Detail your methodology for selecting relevant performance metrics (e.g., time, cost, customer satisfaction) and the processes you use to evaluate and compare the effectiveness of different routing strategies against benchmarks.

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How do you stay current with trends and advancements in data science?

Mention that you regularly read industry publications, attend conferences, participate in online courses, and engage in data science communities. Continued learning is crucial to implement cutting-edge practices in your work.

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What do you consider the biggest challenge in operational research today?

Reflect on the challenges like data quality, dynamic environments, or integrating new technologies. Offer insights into how you would address these challenges based on your background and experience.

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How do you prioritize tasks and manage time effectively in your projects?

Discuss your time management strategies, such as setting clear deadlines, using project management tools, and prioritizing tasks based on impact and urgency. Provide a brief example of how this worked in a specific project.

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MATCH
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SENIORITY LEVEL REQUIREMENT
TEAM SIZE
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HQ LOCATION
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EMPLOYMENT TYPE
Full-time, hybrid
DATE POSTED
March 29, 2025

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