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Senior Data Scientist - Relay Network

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 power nearly every part of our network — from forecasting parcel volumes, to pricing and planning courier capacity, to understanding and improving the economics of our operation.

We’re hiring a Senior Data Scientist to help us model and optimise Relay’s end-to-end network. This role spans across domains, touching forecasting, operations, and commercial planning, and is ideal for someone who thrives on applying models in ambiguous, real-world environments.

You’ll work with squads across routing, sortation, first mile, middle mile, last mile, marketplace, and commercial functions to help forecast demand, plan resources, and drive sustainable growth. You’ll also bring together data from across the business, often fragmented or messy, and use smart tooling, automation, and AI to transform it into usable insight.

You’ll need to be hands-on and pragmatic; it’s a high-impact role with strong exposure to leadership and decision-making across the business.

What you’ll do

  • Design, prototype, and deploy models to support demand forecasting, resource planning, and strategic decision-making

  • Build and own financial and operational models that help simulate trade-offs across the Relay network

  • In partnership with MLE and our Staff Network Data Scientist, orchestrate and automate model pipelines in production, making sure our tools scale as we grow

  • Collaborate with analysts, engineers, and product managers to embed models into decision processes and tooling

  • Leverage AI and programmatic techniques to extract structure from messy or ambiguous data sets

  • Translate business questions into analytical problems and analytical results into actionable recommendations

  • Act as a thought partner for commercial, operations, and finance leads — bringing a scientific lens to planning and growth questions

What we’re looking for

  • 6+ years of experience in data science, with a strong record of delivering models into production

  • Deep experience with Python and SQL

  • Strong foundations in statistics and probability, with experience applying them in operational and/or financial contexts

  • Comfort working in ambiguity and navigating messy or incomplete data

  • Experience with forecasting, scenario modelling, and financial modelling (including partnering with Finance and Commercial teams and their models (in Excel, Google Sheets))

  • 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 in logistics, marketplaces, or similarly complex operational businesses

  • Experience using LLMs or AI tools to structure and extract meaning from unstructured data

  • Experience automating workflows and deploying model pipelines (e.g. Airflow, dbt, MLFlow, or similar)

  • Exposure to business planning, pricing, or commercial decision-making

  • Familiarity with geospatial data

  • Experience in fast-scaling startups or operational teams

We're flexible on experience - if you’re an experienced and pragmatic data scientist, with a track record of driving impact, we’d love to hear from you.

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

$100000 / YEARLY (est.)
min
max
$80000K
$120000K

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 - Relay Network, Relay Technologies

Are you ready to take the leap as a Senior Data Scientist at Relay Network in London? Join our mission to revolutionize e-commerce logistics while making a positive impact on the environment and communities. At Relay, we are dedicated to creating a sustainable logistics network that’s designed for the future of commerce, putting control back in the hands of consumers. In this role, you will leverage your data science expertise to model and optimize our end-to-end network. With your experience in forecasting and resource planning, you’ll collaborate with various teams to drive sustainable growth and improve our operational efficiency. You’ll tackle messy data sets head-on, using advanced techniques to transform raw data into actionable insights that directly influence strategic decision-making. Whether you’re designing innovative models or automating pipelines, your hands-on approach and strategic mindset will be key to your success here. As a Senior Data Scientist, you’ll play a vital role in shaping the future of how packages are delivered, ensuring that sustainability and efficiency are at the forefront of every decision. If you thrive in dynamic, high-impact environments and are excited about driving change through data, Relay Network is where you belong!

Frequently Asked Questions (FAQs) for Senior Data Scientist - Relay Network Role at Relay Technologies
What are the main responsibilities of a Senior Data Scientist at Relay Network?

As a Senior Data Scientist at Relay Network, your main responsibilities will include designing and deploying models that support demand forecasting and resource planning. You'll collaborate with cross-functional teams to embed your findings into decision-making processes and help drive sustainable growth through actionable insights.

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What qualifications are required for the Senior Data Scientist position at Relay Network?

To qualify for the Senior Data Scientist role at Relay Network, candidates should have at least 6 years of experience in data science, with a strong background in Python and SQL. A solid foundation in statistics, along with experience in forecasting and financial modeling, is also essential. Effective communication skills are necessary for explaining results to non-technical stakeholders.

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How does a Senior Data Scientist contribute to sustainability efforts at Relay Network?

A Senior Data Scientist at Relay Network contributes significantly to sustainability efforts by optimizing logistics operations using data-driven insights. By modeling trade-offs and forecasting demand, you’ll help reduce carbon emissions and costs while improving delivery efficiency, aligning perfectly with Relay's mission for a sustainable future.

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What tools and technologies are used by Senior Data Scientists at Relay Network?

Senior Data Scientists at Relay Network use a variety of tools including Python for coding, SQL for data handling, and various AI tools for analyzing complex datasets. Familiarity with tools like Airflow, MLFlow, and data visualization software helps in effectively automating workflows and presenting insights.

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What opportunities for growth and development does Relay Network offer to a Senior Data Scientist?

Relay Network provides a culture of learning and professional growth for Senior Data Scientists. You’ll have opportunities to take ownership of projects, participate in team socials, and engage in continuous learning initiatives that enhance your skills and career progression.

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Common Interview Questions for Senior Data Scientist - Relay Network
Can you explain your experience with forecasting models in data science?

When discussing your experience with forecasting models, emphasize specific techniques you've used, such as time series analysis or machine learning models. Be ready to illustrate how your forecasts have impacted decision-making in previous roles, ideally with quantifiable results.

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How do you handle messy or incomplete data?

When faced with messy data, describe your approach of systematically cleaning and preprocessing it. This includes techniques like data imputation for missing values, normalization, and applying tools that help structure the data for analysis. Highlight your problem-solving skills in overcoming such challenges.

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What role does collaboration play in your work as a Senior Data Scientist?

Stress the importance of collaboration in your role as a data scientist. Share examples of how you’ve worked with analysts, engineers, and product managers to integrate models into tools and workflows. This shows that you value teamwork and have experience driving business impact across departments.

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Describe a project where you used Python for data analysis.

Discuss a specific project where you've utilized Python for data analysis, including the libraries you used (e.g., pandas, NumPy). Outline the problem you solved, the data you analyzed, and the insights you generated, along with how they were applied in a real-world context.

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How do you ensure your models are scalable?

Talk about strategies for ensuring scalability in your models, such as employing modular coding practices and using cloud services for deployment. Mention your experience with model versioning and how you incorporate feedback loops to continually improve the model performance.

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What statistical methods do you find most useful in operational contexts?

Discuss statistical methods such as regression analysis or hypothesis testing that you find most useful in operational contexts. Provide examples of how you’ve applied these methods to derive insights that shaped business strategies effectively.

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Can you describe a time when you communicated technical results to a non-technical audience?

Share a concrete example of a situation where you had to present complex data findings to a non-technical audience. Focus on how you simplified the concepts, used visuals, and engaged them in understanding the implications of the data for decision-making.

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What experience do you have in automating data workflows?

Describe your experience with automating data workflows, including the tools and technologies used (such as Airflow or similar). Highlight a specific project where automation led to increased efficiency and enhanced data accuracy in your analytics processes.

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How do you keep updated with the latest trends in data science?

Convey your commitment to continuous learning by mentioning resources you rely on, such as online courses, webinars, industry conferences, or research papers. Show that you’re proactive about staying informed of trends relevant to your role as a Senior Data Scientist.

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What interests you about working at Relay Network?

Express your enthusiasm for Relay Network’s mission to transform e-commerce logistics sustainably. Share specific aspects of the role that excite you, such as the opportunity to apply data science in a meaningful way that impacts the environment and addresses real-world challenges.

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Full-time, hybrid
DATE POSTED
March 29, 2025

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