Professional / D - Data Science
Role details
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Job description
Position: Data Scientist Department: Logistics Reporting to: Data Science Team Lead Location: Berlin Hybrid role: 3 days a week from our office & 2 days working from home
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
Join our Courier Pay & Incentives team as a Data Scientist, where you will lead efforts in optimising driver pay. In this role, you will leverage advanced analytics and machine learning techniques to analyse driver performance data, design incentive programs, and develop predictive models to maximise earnings while maintaining cost-efficiency and ensuring timely deliveries. You will be part of an established team of data scientists with experience in these areas, working closely with multiple cross-functional teams to build the next generation of algorithms that will scale our business.
Working within Logistics Technology, your focus sits at the intersection of economics, real-time ML, and logistics operations. You will help improve real-time courier incentive systems that operate under strict latency and fairness constraints. You'll contribute to model improvements from development through to live production deployment, all while further developing your skills under the guidance of senior team members.
These are some of the key components to the position:
- Develop and validate ML models for courier compensation, including dynamic earnings floors, surge and boost mechanisms, and engagement-based incentive programs
- Build features from operational data and design experiments to measure model performance improvements
- Execute causal experimentation at scale, utilising A/B testing, switchback experiments, and geo-based designs to measure the true impact of pay changes and incentive structures
- Apply engineering best practices including clean code, version control, unit testing, and production monitoring
- Translate analytics outputs into clear, actionable insights for stakeholders using data visualisation and accessible language
- Collaborate with ML Engineers and Operations Research Scientists on cross-functional projects
- Identify opportunities to automate retraining, validation, and evaluation pipelines
- Monitor and maintain predictive performance in live production environments
What will you bring to the team?
- Hands-on experience building and validating ML models in production, with an asset being prior exposure to real-time or low-latency systems.
- Proficiency in Python and SQL for data analysis and model development
- Strong understanding of supervised ML techniques (regression, classification, gradient boosting) and time-series modeling.
- Solid conceptual grounding in experimental design, offline validation, and marketplace experimentation (such as switchback testing or interference-aware designs)
- An interest or background in incentive design, dynamic pricing, or labor economics, allowing you to reason about behavioral responses and fairness trade-offs
- Exposure to ML Ops practices including version control (Git), data pipelines, and model monitoring in production
- Interest in logistics and real-world operational problems is a plus
At JET, this is how we play
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.
Being the best at what we do isn't just about delivering on our strategy. It's a competition for something incredibly valuable - our customers' choice. Every time a customer decides where to order, they're picking a side.
At the heart of the JET Customer League are our values and behaviours. They guide every interaction, every decision, every innovation. These are the actions we need to perform consistently and brilliantly, to surpass the competition and earn our customers' loyalty, again and again.
Fun, fast-paced and supportive, the JET culture is about movement, growth, helping one another to succeed and celebrating wins. By truly living our values and embodying our behaviours, we're building a customer-first culture which enables us to 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-KF1
Requirements
- Hands-on experience building and validating ML models in production, with an asset being prior exposure to real-time or low-latency systems.
- Proficiency in Python and SQL for data analysis and model development
- Strong understanding of supervised ML techniques (regression, classification, gradient boosting) and time-series modeling.
- Solid conceptual grounding in experimental design, offline validation, and marketplace experimentation (such as switchback testing or interference-aware designs)
- An interest or background in incentive design, dynamic pricing, or labor economics, allowing you to reason about behavioral responses and fairness trade-offs
- Exposure to ML Ops practices including version control (Git), data pipelines, and model monitoring in production
- Interest in logistics and real-world operational problems is a plus