Senior Data Scientist - (Global Search, Consumer)

Google Chrome Microsoft Edge Apple Safari Mozilla Firefox Senior Data Scientist - (Global Search, Consumer)Full-timeCompany DescriptionAs 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 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.Job DescriptionWe are on the lookout for a Senior Data Scientist - (Global Search, Consumer) to join the Search Ranking team within our Global Search tribe. If you thrive at the intersection of cutting-edge deep learning research and high-traffic production systems — and are excited about autonomous AI-driven experimentation — this role is for you.Our search functionality spans more than 60 countries and 35 languages, facilitating over 80 million searches daily across four continents. The ranking systems you build will directly shape what millions of customers see every time they open the app.Your mission:Own the Ranking Stack End-to-End: Design, build, and productionalize deep neural ranking models — including DCN-V2, MMoE, and Two-Tower architectures — operating at high throughput and low latency in production. You will own the full lifecycle: from offline experimentation and evaluation to monitoring, and iterative improvement.Drive Agentic ML Research: Embrace and champion the shift from manual experimentation to prompt-driven orchestration. You will leverage LLM coding agents (e.g., Claude Code, Gemini) to autonomously iterate on feature engineering and Learning to Rank (LTR) architectures. Inspired by the auto-research paradigm, you will design overnight experiment pipelines and review the outputs of hundreds of autonomous runs to identify signals quickly.Lead Feature Engineering and Model Architecture Innovation: Apply your deep expertise in ranking signals, feature stores, and embedding-based retrieval to push the quality of our rankers. Propose and validate new model architectures grounded in the latest research, translating academic advances into production-grade systems.Ensure Production Reliability: Maintain rigorous standards for model health in production. You will own monitoring for model drift, latency degradation, and feature pipeline integrity, and act quickly when signals deviate — keeping our ranking quality high for users across all markets.Collaborate Across Disciplines: Work as a technical partner with Backend Engineers, Data Engineers, and Product Managers to deliver end-to-end improvements. Translate complex ML trade-offs into clear narratives for non-technical stakeholders, and contribute to shaping the team's roadmap.Raise the Bar: Mentor junior and mid data scientists, drive best practices in experimentation rigor and code quality, and actively contribute to a culture of learning — especially around emerging agentic development workflows.QualificationsMaster's degree (or Bachelor's with 6+ years of work experience) in Computer Science, Mathematics, Physics, or a related quantitative field. 4+ years of industry experience as a Data Scientist or Machine Learning Engineer applying ML in high-traffic production environments.Deep Learning Ranking & LTR: Hands-on, production-proven experience implementing modern deep learning ranking architectures — DCN-V2, MMoE, Two-Tower — with strong command of multi-task learning, cross-feature interactions, and embedding optimization at scale. Solid foundation in LTR methods (pointwise, pairwise, listwise), offline evaluation metrics (NDCG, MRR), and the challenges of bridging offline metrics...