Data Scientist - (Logistics, Optimization)

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.

We are on the lookout for a Data Scientist to join the Logistics Optimization team on our journey to always deliver amazing experiences. In our Logistics Team, you’ll tackle high-impact challenges that make last-mile delivery efficient, affordable, and sustainable. Your work will directly improve experiences for riders, end customers, and merchants across the globe. Each enhancement you contribute will help Delivery Hero optimize delivery operations, supporting expansion into new areas like grocery and retail. The Optimization Tribe's purpose is to maximize Delivery Hero's logistics performance. We achieve this by owning and continuously improving the sophisticated algorithm that solves the real-time vehicle routing problem, assigning orders efficiently every minute. This directly impacts DH's core efficiency and customer satisfaction KPIs, influencing decisions for stakeholders from Operations to Product. As a Data Scientist, your value lies in tackling these fascinating problems head-on and building ML products which shape the algorithm's logic and decisions to meet our long-term goals of best-in-class efficiency and service, making a tangible impact across the Delivery Hero network. Design & Innovate: Lead the conceptualization and design of advanced modeling solutions (using a mix of ML, Statistics and Math) to tackle complex, large-scale Logistics challenges, ensuring alignment with business value and stakeholder needs. Build & Automate: Take ownership of developing, implementing and automating robust data science models and pipelines, including feature generation, retraining, and prediction deployment, leveraging tools like BigQuery and Spark as needed. Solve & Collaborate: Actively drive technical discussions and problem-solving sessions, contributing significant expertise and innovative ideas to overcome the toughest modeling hurdles alongside your Data Science peers and squad lead. Drive Business Impact: Translate sophisticated analytical findings and model outcomes into clear, actionable insights for stakeholders, demonstrably driving value and improvements in key business metrics. Shape Data Strategy: Proactively engage with Data & ML Engineering and Tech teams to define critical data requirements and influence technical roadmaps, ensuring the necessary data infrastructure for impactful projects. Contribute & Elevate: Make a significant impact within our fast-paced, global organization by delivering high-quality solutions, sharing knowledge, and contributing to the team's overall growth and best practices.

Applied Machine Learning Mastery: You have significant experience (ideally 3+ years) designing and implementing diverse machine learning models (e.g., regression, classification, tree-based ensembles) to solve real-world business problems, backed by a strong theoretical foundation in statistics and probability. Production ML Engineering: You possess expert-level Python skills (incl. pandas, scikit-learn, etc.), proficiency in SQL, and demonstrable experience building robust, maintainable, and automated ML pipelines using Big Data technologies (e.g., BigQuery, Spark) and workflow orchestration tools (e.g.,