Senior Data Scientist - Quick Commerce

As the world’s pioneering local delivery platform, our mission is to deliver an amazing experience, fast, easy, and to your door. We operate in over 70+ countries worldwide, powered by tech, designed by people. As one of Europe’s largest tech platforms, headquartered in Berlin, Germany. Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index. We enable creative minds to deliver solutions that create impact within our ecosystem. We move fast, take action and adapt. No matter where you're from or what you believe in, we build, we deliver, we lead. We are Delivery Hero.

We are on the lookout for a Senior Data Scientist to join our "Quick Commerce Growth Product Line” on our journey to always deliver amazing experiences.

Be part of redefining how customers experience quick commerce. You’ll help build technology that scales our non-food offerings, reaching new market segments and driving revenue growth. By innovating within our Quick Commerce Team, you’ll make Delivery Hero the go-to platform for a broad range of products, helping us grow faster and deliver more value to customers around the world.

At Quick Commerce, we are building the next generation of ranking and personalization systems to power our global quick commerce business. We want every customer to have a truly personalized experience – from the very first search to the final checkout – enriched with live signals that reflect their real-time needs.

As a Senior Data Scientist (Affordability Intelligence Team), you will work side-by-side with Data Scientists, Machine Learning Engineers, and Software Engineers to design, experiment with, and deliver advanced ranking solutions deployed across dozens of countries and millions of customers.

This is a role for someone who has already worked on user-facing personalization, causal inference, and time series problems at scale and is hungry to push boundaries further. You will drive hypotheses, run A/B tests on customer-facing uplift models, and bring robust causal and time-series architectures into production with real business impact. If you’re a strong coder with a hacker mentality and thrive in high-scale applied ML and econometric problems, we’d love to talk.

Your mission:

• Design, experiment, and deploy customer-facing personalisation and uplift models (including personalisation via ranking) to measurably improve affordability perception and user experience at global scale.

• Drive experimentation: formulate hypotheses, analyze A/B tests, and turn insights into production-ready solutions for better targeting and incentive deployment.

• Apply advanced time series and causal inference techniques to model and forecast the supply and demand of incentives.

• Leverage live user signals and context to make affordability interventions more adaptive and dynamic.

• Keep yourself up to date and apply state-of-the-art causal and machine learning models to see what truly works best for our customers and business.

• Collaborate closely with MLEs and Engineers to ensure solutions are scalable, reliable, and fast in production.

• Contribute to the long-term vision of affordability intelligence and personalisation at QC, while delivering short-term wins that unlock measurable business impact.

• Mentor and inspire peers, raising the quality bar for Data Science in causal inference and personalization across the tribe.

• 5+ years of industry experience applying Data Science and Machine Learning in production, ideally in large-scale consumer-facing applications.

• Experience with user-facing personalization systems (including ranking, retrieval, or recommendation systems) – ideally in e-commerce or consumer-tech.

• Expertise in causal inference and uplift modeling for user targeting and intervention strategies.

• Strong statistical foundations and ability to distinguish signal from noise in large-scale experimentation.

• Excellent engineering skills: write clean, maintainable Python code; experience bringing ML models into production with best practices for observability, monitoring, and performance.

• Experience with large-scale experimentation and A/B testing platforms.

• Proven ability to work cross-functionally with engineers and product stakeholders, translating business problems into data science solutions.

• A hacker mentality: pragmatic, hands-on, and comfortable iterating fast to get ranking solutions live.

Nice to have:

• Experience scaling personalization and causal systems across multiple markets and heterogeneous platforms.

• Familiarity with cloud platforms (GCP preferred).

• Contributions to the data science community (conference talks, papers, OSS).

• Experience mentoring other team members and driving knowledge sharing.

We believe diversity and inclusion are key to creating not only an exciting product, but also an amazing customer and employee experience. Fostering this starts with hiring - therefore we do not discriminate on the basis of racial identities, religious beliefs, color, national origin, gender identities or expressions, sexual orientations, age, marital or disability statuses, or any other aspect that makes you, you. We encourage you to let us know if you need any accommodations or specific accessibility support to ensure a smooth interview experience—just include it in your application. You're welcome to share your pronouns (he/she/they) right from the start so we can address you respectfully from our first contact.