Data scientist - Customer data

Just Eat Takeaway.com•Amsterdam, OH

11d

About The Position

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 As a Data Scientist, you will design and productionize features across all JET markets. Focusing on scaling experiments that optimize customer engagement and marketing effectiveness is where you will bring impact. You will apply advanced techniques such as segmentation, churn prediction, recommendation systems, and uplift modeling to improve the customer experience. You’ll work with MarTech platforms, large-scale data, and statistical models, and you’ll collaborate closely with marketing, product, and engineering stakeholders to turn ideas into data and insights into actions. You’ll also ensure that results are clearly communicated, aligned with business priorities, and actionable across different teams and levels of the organization. We expect not just modelling but also a keen understanding of ML engineering and a hands-on approach. You will be a problem solver and not just a data modeller: One of your first challenges will be to drive the implementation of a Next Best Action model to support our Marketing teams with Marketing effectiveness while helping our Customers get the best experience with JET. You will share learnings and contribute to NBA for Partners by collaborating with other DnA teams as well. And you will drive our shift towards an experimentation culture by working closely with Product and Experimentation teams. These are some of the key components to the position: Design and execute end-to-end experiments to improve the customer experience and marketing effectiveness. Optimize our existing data models and support product personalization. Apply uplift modeling, causal inference, and attribution analysis to drive strategic decisions and measure impact. Partner with Marketing, Product, Tech and Experimentation teams to enable and run targeted experiments and improve customer engagement. Translate complex analyses into clear, actionable recommendations for non-technical stakeholders. Promote a culture of evidence-based decision-making and knowledge sharing.

Requirements

Experience as a Data Scientist, ideally in e-commerce, food delivery, or consumer-facing industries.
Proficiency in SQL, Python, and libraries for data science (e.g., pandas, scikit-learn).
Hands-on experience with experimentation methods (A/B testing, causal inference, uplift modeling).
Solid understanding of customer analytics (segmentation, churn prediction, personalization, recommendations).
Excellent communication skills and proven ability to manage stakeholders at different levels.
An analytical mindset with curiosity and creativity to explore new approaches.
Most importantly, excellent at community building and being the glue to a team together

Nice To Haves

Experience with cloud environments (GCP, AWS, Azure) and Google Stack (Vertex AI, Looker ML, BigQuery) is preferred.
Experience with deep learning is an advantage.
Familiarity with MarTech platforms (Braze, Salesforce Marketing Cloud, Adobe) is an advantage.

Responsibilities

Design and execute end-to-end experiments to improve the customer experience and marketing effectiveness.
Optimize our existing data models and support product personalization.
Apply uplift modeling, causal inference, and attribution analysis to drive strategic decisions and measure impact.
Partner with Marketing, Product, Tech and Experimentation teams to enable and run targeted experiments and improve customer engagement.
Translate complex analyses into clear, actionable recommendations for non-technical stakeholders.
Promote a culture of evidence-based decision-making and knowledge sharing.

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