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About the Role

We are seeking a Senior Data Scientist to join the Search Ranking team. This role focuses on designing, building, and productionalizing deep neural ranking models for a high-traffic global search platform, with an emphasis on agentic ML research and autonomous experimentation.

Responsibilities

• Own the Ranking Stack End-to-End: Design, build, and productionalize deep neural ranking models, owning the full lifecycle from offline experimentation to monitoring and iterative improvement.
• Drive Agentic ML Research: Leverage LLM coding agents to autonomously iterate on feature engineering and Learning to Rank (LTR) architectures, designing experiment pipelines and reviewing autonomous run outputs.
• Lead Feature Engineering and Model Architecture Innovation: Apply expertise in ranking signals, feature stores, and embedding-based retrieval to improve ranker quality and validate new model architectures.
• Ensure Production Reliability: Maintain rigorous standards for model health in production, owning monitoring for model drift, latency degradation, and feature pipeline integrity.
• Collaborate Across Disciplines: Work as a technical partner with Backend Engineers, Data Engineers, and Product Managers, translating complex ML trade-offs for stakeholders.
• Raise the Bar: Mentor junior and mid data scientists, drive best practices in experimentation rigor and code quality, and contribute to a culture of learning.

Requirements

• 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.
• 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 bridging offline metrics to online A/B outcomes.
• Proficiency with LLM coding agents and agentic CLI tools (e.g., Claude Code, Gemini) as development tools 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.
• 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 including 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.
• Comfortable navigating ambiguity and translating broad business objectives into well-scoped data science projects.
• Accountable for outcomes, not just outputs.
• 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.

Skills

• Deep Learning Ranking
• Learning to Rank (LTR)
• DCN-V2
• MMoE
• Two-Tower architectures
• Multi-task learning
• Embedding optimization
• Agentic & AI-Assisted Development
• LLM coding agents
• Claude Code
• Gemini
• Python
• PyTorch
• TensorFlow
• scikit-learn
• SQL
• dbt
• GCP
• AWS
• PySpark
• Scala
• MLOps
• CI/CD for ML pipelines
• Metaflow
• Experiment tracking
• Model registry
• Production monitoring
• Drift detection
• Latency tracking
• Data quality alerting

Location

• Berlin, Germany

Work Type

• Hybrid

Experience Level

• Senior
• 4+ years of industry experience

Education Level

• Master's degree in Computer Science, Mathematics, Physics, or a related quantitative field
• Bachelor's degree with 6+ years of work experience in Computer Science, Mathematics, Physics, or a related quantitative field

Benefits

• 27 days holiday with an extra day on 2nd and 3rd year of service
• 1.000 € Educational Budget
• Language Courses
• Parental Support
• Access to Udemy Business platform
• Health Checkups
• Meditation & Gym
• Employee Share Purchase Plan
• Sabbatical Bank
• Public Transportation Ticket Discount
• Life & Accident Insurance
• Corporate Pension Plan
• Digital Meal Vouchers
• Food Vouchers
• Support with relocation to Berlin

About the Company

• 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.

Equal Opportunity

• 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.