Data Scientist

Position:Data Scientist
Department:AI Growth
Reporting to:Data Science Manager
Location:London or Amsterdam
Hybrid role: 3 days a week from our office & 2 days working from home

Ready for a challenge?

Then Just Eat  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.

Join our AI Growth team and help build the intelligence behind Just Eat's marketplace, powering personalised experiences for tens of millions of customers across 14 countries. This is your opportunity to deliver end-to-end machine learning solutions that directly impact customer engagement and order growth.

We're building JET's foundation model platform, developing embedding models for search and recommendations, and creating intelligent targeting systems for personalised offers and notifications. We're looking for someone who can live our behaviours of lead, deliver and care while bringing technical excellence and innovation.

This role sits at the intersection of cutting-edge AI and real-world business impact. You'll work on everything from fine-tuning large language models to designing sophisticated recommender systems, all while collaborating with ML engineers, product teams, and commercial stakeholders.

We need someone who can challenge assumptions, translate ambiguous business problems into elegant technical solutions, and ship production-quality ML systems that make a measurable difference to our customers and partners.

• Lead the development and deployment of ML/AI solutions including embedding models, fine-tuned LLMs, and ranking systems that drive engagement and orders while raising the bar for technical excellence.
• Apply generative AI and LLM techniques to personalisation challenges, generating customer and partner representations that improve search relevance and app experiences.
• Own your results by designing, running and interpreting A/B experiments with statistical rigour, measuring real impact on business metrics and holding yourself accountable.
• Collaborate with ML engineers to product ionise models, implementing MLOps best practices and maintaining monitored pipelines that deliver consistent value.
• Break down silos by translating complex business questions into clear modelling approaches and communicating results effectively to product and commercial stakeholders.
• Be determined to take end-to-end ownership of well-scoped work streams, independently framing problems, choosing approaches, running experiments and presenting findings.
• Move fast by writing production-quality Python code and efficient SQL for data pipelines and analyses that can scale across our marketplace.
• Contribute to JET's foundation model platform and personalised targeting systems, pushing boundaries to create lasting impact across millions of customer interactions.
• Set clear goals by designing experiments that influence commercial decisions while ensuring statistical validity and actionable insights.
• Aim higher by staying current with advances in search, retrieval, recommendations and LLM applications, bringing fresh ideas to drive the AI Growth vision forward.

• Proven track record delivering end-to-end ML solutions from problem framing through data exploration to production deployment and experiment measurement, demonstrating your commitment to achieving goals.
• Hands-on expertise in search, retrieval and recommendation techniques including embedding-based approaches, learning-to-rank, and vector similarity search with measurable business impact.
• Practical experience applying LLMs in production environments, including prompt engineering, fine-tuning, structured output validation and assessing generative output quality.
• Strong experimentation skills with ability to design and interpret A/B tests, reason about statistical significance, and understand the gap between offline and online performance.
• Production-grade Python coding abilities that go beyond notebooks, writing clean, testable code suitable for engineering workflows and collaboration with technical teams.
• Proficient SQL skills across complex data warehouses, including partitioning, window functions, and large-table joins, with focus on query efficiency and data quality.
• Excellent problem-framing and communication skills to translate ambiguous business questions into modelling approaches and explain technical results to non-technical stakeholders based on respect and mutual support.
• Self-starter attitude comfortable with autonomy and ambiguity, thriving in fast-paced environments where you can build rapidly, test rigorously and roll out successes at scale.
• Strong collaboration skills to work effectively with senior data scientists,…