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 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 Description
We 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:
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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.
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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.
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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.
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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.
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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.
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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.
Qualifications
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Master'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.
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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 to online A/B outcomes.
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Agentic & AI-Assisted Development: Proficiency with LLM coding agents and agentic CLI tools (e.g., Claude Code, Gemini) as first-class tools in your development workflow — not just for boilerplate, but for autonomous experiment generation, architecture prototyping, and rapid iteration. Familiarity with the auto-research paradigm and comfort reviewing large volumes of autonomously generated experiment results.
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Technical Depth & MLOps: Expert in Python and its ML ecosystem (PyTorch, TensorFlow, scikit-learn). Comfortable with SQL (dbt), cloud environments (GCP or AWS), and big-data processing at scale (PySpark, Scala). Strong command of the full ML lifecycle — feature stores, vector databases, model versioning, A/B experimentation frameworks, and deployment to high-throughput, low-latency serving infrastructure. Hands-on experience with MLOps practices: CI/CD for ML pipelines, Metaflow, experiment tracking, model registry, and production monitoring covering drift detection, latency tracking, and data quality alerting.
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Problem-Solving & Ownership: Comfortable navigating ambiguity and translating broad business objectives into well-scoped data science projects. You hold yourself accountable for outcomes, not just outputs.
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Collaborative Spirit: Demonstrated ability to work effectively in cross-functional, globally distributed teams. Strong communication skills to articulate model behavior, experiment results, and trade-offs to both technical and non-technical audiences
Additional Information
Ensuring you and all our Heroes are looked after, happy, and healthy is always on the menu. Because if you’re in good shape, then we’re in good shape.
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Make the most of our hybrid working model and join the team for face-to-face connection and collaboration in our beautiful Berlin campus 2 days a week
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We offer 27 days holiday with an extra day on 2nd and 3rd year of service
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We will support you in developing yourself and your career growth opportunities: 1.000 € Educational Budget, Language Courses, Parental Support and access to the Udemy Business platform to explore a variety of online courses.
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Get moving and release those wonderful, mind-boosting endorphins: Health Checkups, Meditation & Gym.
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Cash. Dough. Cheddar. Whatever you call it, we’ll help you with it: Employee Share Purchase Plan, Sabbatical Bank, Public Transportation Ticket Discount, Life & Accident Insurance, Corporate Pension Plan
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The power of getting together over some food is unrivaled. Here are a few ways to help you do that. All the yum: Digital Meal Vouchers and Food Vouchers.
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Wondering what relocating to Berlin is like? In this article, we’ve put together 10 things you should know about moving to Berlin and how Delivery Hero can support you. You can also visit our relocation hub and check out more information about moving to Berlin.
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Ready to prepare for your interview? Check out the list of the 5 most common interview questions and answers created in collaboration with our recruiters.
Ready to join our team? If you’re excited to grow, collaborate and be part of the world’s leading delivery platform, we’d love to hear from you. Apply today!
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 let us know with an email to our Inclusion Officer at [email protected].
Severely disabled applicants with equal qualifications will be given preferential consideration.
You're welcome to share your pronouns (he/she/they) right from the start so we can address you respectfully from our first contact.
