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Staff Data Scientist, Dmarts - Quick Commerce (Data Scientist)

Delivery Hero SE

Alemania📅 30/7/2026

Descripción

Company Description 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 around 65 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 push hard, learn quickly and stay human along the way. It’s this wonderful mix of high performance and real community that makes Delivery Hero a place where ambition and belonging grow side by side. If you’re curious, collaborative and ready to dive deep into meaningful work, you’ll fit right in. Job Description We are on the lookout for a Staff Data Scientist in Quick Commerce to join our team and help us take our forecast and operations to the next level. 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. The team's mission is to improve vendors' experience and bring value to the critical path of supply chain process through data science and data engineering. You will be working with an international and experienced team, shaping the experience for millions of customers who order daily through our platform. You’ll bring in World-Class AI and ML Expertise to help design, build, and maintain the features and ML models that behind our operations. You'll drive engineering excellence and collaborate closely with our fellow colleagues. Join us in building and maintaining this mission-critical service! - Develop, test, and productionize forecasting algorithms using state-of-the-art machine learning, statistical inference, a
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