Staff Data Scientist, Dmarts - 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 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. Deep analysis. Smarter systems. Real users. As a Staff Data Scientist, you'll lead the forecasting and optimization models that decide how our Dmarts and local shop vendors source and stock their products. You'll set the ML standards for the squads in your domain and be the technical leader behind their models and architecture. Your work will help keep shelves stocked, cut waste, and make our supply chain more capital-efficient. The team's mission is to improve the vendor experience and bring value to the critical path of the supply chain process through data science and data engineering. You'll work with an international, experienced team, shaping the experience for millions of customers who order daily through our platform. 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. Develop, test, and productionize forecasting algorithms using machine learning, statistical inference, and optimization models. Act as the technical leader for ML projects in your domain and own their model and architecture design. Set ML best practices and standards for the squads in your domain, and drive their adoption. Review the work of data scientists in your domain and mentor them. Work with product and engineering leads to set the vision and goals for your squads. Identify new technologies and opportunities to improve the forecasting and operations systems you build for stakeholders. 9+ years of experience in Data Science designing robust end-to-end data workflows, and at least 5 years of experience with forecasting techniques or optimization. Proven track record owning the data science lifecycle (design, evaluation, deployment, monitoring) for models in production. Experience setting ML best practices and driving their adoption across multiple squads. Solid programming skills in Python, Docker, and cloud platforms (AWS or GCP). Hands-on experience with AI frameworks (e.g., TensorFlow, PyTorch) and with LLMs. Ability to build consensus among stakeholders and data scientists, lead without formal authority, and communicate results clearly in English to technical and non-technical audiences. — Published by Delivery Hero. Apply on the employer's own posting.