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About the Role

As a Senior Data Scientist (Global Search, Consumer), you will own the deep learning ranking models behind the search services that power every Delivery Hero platform. You will also lead our move to agentic ML research, using LLM coding agents to run hundreds of overnight experiments and turn the strongest signals into ranking gains in production. Your work will directly shape what millions of customers see every time they open the app, enhancing customer satisfaction and driving global growth and profitability.

Responsibilities

Own the ranking stack end to end: design, build, and productionize deep neural ranking models for high-throughput, low-latency serving.
Lead agentic ML research: use LLM coding agents to autonomously iterate on feature engineering and Learning to Rank (LTR) architectures.
Improve ranker quality through feature engineering and model architecture work, applying expertise in ranking signals, feature stores, and embedding-based retrieval.
Keep production models healthy by owning monitoring for model drift, latency degradation, and feature pipeline integrity.
Partner with Backend Engineers, Data Engineers, and Product Managers to deliver end-to-end improvements.
Mentor junior and mid-level data scientists and set the standard for experimentation rigor, code quality, and agentic development workflows.

Requirements

A Master’s degree in Computer Science, Mathematics, Physics, or a related quantitative field (or a Bachelor’s with 6+ years of work experience), plus 4+ years as a Data Scientist or Machine Learning Engineer applying ML in high-traffic production environments.
Production-proven experience with deep learning ranking architectures (DCN-V2, MMoE, Two-Tower), including multi-task learning, cross-feature interactions, and embedding optimization at scale.
Solid foundation in LTR methods (pointwise, pairwise, listwise), offline metrics (NDCG, MRR), and the challenges of bridging offline metrics to online A/B outcomes.
Proficiency with LLM coding agents and agentic CLI tools as first-class development tools for autonomous experiment generation, architecture prototyping, and rapid iteration.
Familiarity with the auto-research paradigm and comfort reviewing large volumes of generated experiment results.
Expert Python skills across the ML ecosystem (PyTorch, TensorFlow, scikit-learn).
Working knowledge of SQL (dbt), GCP or AWS, and big-data processing (PySpark, Scala).
Hands-on MLOps across the full lifecycle: feature stores, vector databases, model versioning and registry, Metaflow, CI/CD for ML pipelines, experiment tracking, A/B frameworks, low-latency deployment, and production monitoring for drift, latency, and data quality.
Comfort turning broad business objectives into well-scoped data science projects, with accountability for outcomes, not just outputs.
Experience working in cross-functional, globally distributed teams.
Ability to explain model behavior, experiment results, and trade-offs to technical and non-technical audiences.

Skills

Deep Learning Ranking Models (DCN-V2, MMoE, Two-Tower)
Multi-task learning
Cross-feature interactions
Embedding optimization
Learning to Rank (LTR) methods
Offline metrics (NDCG, MRR)
LLM coding agents
Agentic CLI tools
Auto-research paradigm
Python
PyTorch
TensorFlow
scikit-learn
SQL
dbt
GCP
AWS
PySpark
Scala
MLOps
Feature stores
Vector databases
Model versioning
Model registry
Metaflow
CI/CD for ML pipelines
Experiment tracking
A/B frameworks
Low-latency deployment
Production monitoring

Location

Berlin, Germany

Work Type

Hybrid

Experience Level

Senior
4+ years as a Data Scientist or Machine Learning Engineer

Education Level

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

Benefits

27 days holiday with an extra day on 2nd and 3rd year of service
1.000 € Educational Budget
Language Courses
Parental Support
Udemy Business platform access
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
Relocation support for 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].
You're welcome to share your pronouns (he/she/they) right from the start so we can address you respectfully from our first contact.