Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Team Leader - Data Science

London
1 week ago
Create job alert

Ready for a challenge?

Then Just Eat Takeaway.com might be the place for you. We’re a leading global online delivery platform, and our vision is to empower everyday convenience. 

Whether it’s a Friday-night feast, a post-gym poke bowl, or grabbing some groceries, our tech platform connects tens of millions of customers with hundreds of thousands of restaurant, grocery and convenience partners across the globe.

About this role:

This is more than a management role; it's a leadership opportunity. You will lead a diverse team of Data Scientists and Operations Research Scientists across Europe and North America, acting as the primary architect of their culture. Your mission is to build an environment of high psychological safety where curiosity and experimentation thrive, and where intelligent failures are celebrated as learning opportunities. You will be the coach and mentor who guides the team through the inherent ambiguity of research and discovery, empowering them to tackle immense technical challenges and deliver extraordinary results while building a cohesive, collaborative unit that transcends geographic boundaries.

You won't do this alone. You will act as a key strategic partner to Product and Engineering, translating high-level business goals into a clear, actionable technical roadmap for your team. You will be the bridge between the business and the technical world, connecting with and influencing stakeholders to ensure your team's work is aligned with our business goals, while championing our commitment to responsible innovation and ensuring that principles of fairness and ethical AI are at the core of everything your team creates.

What will you bring to the team?

Hard skills:

Technical Expertise: Advanced proficiency in data science, machine learning, and/or operations research methodologies, with extensive experience applying these techniques in production environments.

Project Leadership: Proven experience leading complex technical projects, with a track record of successfully evolving existing systems and innovating with new solutions.

MLOps & Modern Practices: Strong understanding of modern data science and MLOps practices, including model lifecycle management, experimentation, and CI/CD.

Core Programming & Software Craftsmanship: Proficiency in Python and SQL, with a strong grasp of software development best practices (testing, git, code reviews).

Real-Time Systems Experience: Experience with real-time data integration and machine learning frameworks is highly beneficial.

Modern AI Acumen: Familiarity with the principles and applications of modern AI, including Large Language Models (LLMs) and generative AI, is a strong plus.

Domain-Specific Knowledge: A solid understanding of forecasting techniques is required; experience with mathematical optimization is a strong plus.

Soft skills:

Exceptional leadership and mentorship skills: A genuine passion for cultivating talent. You have a proven track record of developing team members through coaching and creating clear, compelling career paths for both individual contributors and future managers.

A constructive and resilient mindset: The ability to step into a complex situation, create clarity, and drive a team towards a clear and ambitious goal.

Intellectual Humility: A confident awareness of your own limitations and the ability to lead a team of deep experts. You foster a meritocracy of ideas and are comfortable saying "I don't know."

A holistic project approach: The ability to manage technical debt, stakeholder expectations, and long-term strategic roadmaps.

Strong critical analysis: The ability to analyze technical approaches, assumptions, and business impact, with the drive to make tough decisions and find simple, effective solutions.

Expertise in agile and remote-first environments: Exceptional collaborative skills are a must.

Excellent communication skills: The ability to advise, challenge, and influence senior stakeholders.

At JET, this is on the menu:

Our teams forge connections internally and work with some of the best-known brands on the planet, giving us truly international impact in a dynamic environment.

Fun, fast-paced and supportive, the JET culture is about movement, growth and about celebrating every aspect of our JETers. Thanks to them we stay one step ahead of the competition.

Inclusion, Diversity & Belonging

No matter who you are, what you look like, who you love, or where you are from, you can find your place at Just Eat Takeaway.com. We’re committed to creating an inclusive culture, encouraging diversity of people and thinking, in which all employees feel they truly belong and can bring their most colourful selves to work every day.

What else is cooking?

Want to know more about our JETers, culture or company? Have a look at our career site where you can find people's stories, blogs, podcasts and more JET morsels.

Are you ready to take your seat? Apply now!

#LI-CB2

Related Jobs

View all jobs

Senior Team Leader - Data Science

Lead Product Data Analytics

Lead Product Data Analytics

Data Analyst

Data Analyst

Environmental Data Analyst - 12 month FTC

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.