Senior Data Scientist - (Global Search, Consumer)

Delivery Hero; Berlin; Hybrid; EUR 110.000 - 140.000; Vollzeit

Benefits dieser Stelle

Hybrid work model

27 days holiday

Educational budget

Language courses

Parental support

Udemy Business access

Health checkups

Meditation

Gym access

Share purchase plan

Sabbatical bank

Transit discount

Life and accident insurance

Pension plan

Meal vouchers

Relocation hub

Zusammenfassung

Delivery Hero is seeking a Senior Data Scientist for Global Search, Consumer, to join the Search Ranking team. You will bridge cutting‑edge deep learning with high‑traffic production systems, shaping what customers see in our app across 60+ countries and 35 languages.

The role emphasizes autonomous experimentation using LLM coding agents, feature stores, and embedding‑based retrieval, with a strong focus on production monitoring, A/B testing, and cross‑functional collaboration in Berlin.

Qualifikationen

• 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 in high‑traffic production environments.
• Hands‑on experience with modern deep learning ranking architectures (e.g., DCN‑V2, MMoE, Two‑Tower) and LTR methods.
• Proficiency with LLM coding agents and agentic CLI tools (Claude Code, Gemini) and auto‑research paradigms.
• Expertise in Python ML stack (PyTorch, TensorFlow, scikit‑learn), SQL, cloud environments (GCP or AWS), and big‑data processing (PySpark, Scala); MLOps, CI/CD for ML, experiment tracking, model registry, and production monitoring.

Aufgaben

• Own the Ranking Stack end‑to‑end: design, build, and productionalize deep neural ranking models with high throughput and low latency.
• Lead agentic ML research: leverage LLM agents to autonomously iterate on feature engineering and Learning‑to‑Rank architectures.
• Design overnight experiment pipelines and review hundreds of autonomous runs to identify signals quickly.
• Lead feature engineering and model architecture innovation using ranking signals, embedding optimization, and modern architectures.
• Ensure production reliability with monitoring for drift, latency, and data quality; maintain high ranking quality across markets.
• Collaborate with Backend/Data Engineers and Product Managers to translate ML trade‑offs to non‑technical stakeholders; contribute to roadmap.
• Mentor junior/mid data scientists and promote rigorous experimentation practices and code quality.

Kenntnisse

Python

PyTorch

TensorFlow

LTR

ML Experimentation

Cross‑functional collaboration

Ausbildung

Master's degree in CS/Math/Physics

Bachelor +6 years experience

Tools

SQL

dbt

GCP

AWS

PySpark

Scala

Jobbeschreibung

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.

Responsibilities

• 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. 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. Leverage LLM coding agents (e.g., Claude Code, Gemini) to autonomously iterate on feature engineering and Learning‑to‑Rank architectures. Design overnight experiment pipelines and review outputs of hundreds of autonomous runs to identify signals quickly.
• Lead Feature Engineering and Model Architecture Innovation: Apply 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. Own monitoring for model drift, latency degradation, and feature pipeline integrity, and act quickly when signals deviate to keep 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 level 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

• 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.
• Deep Learning Ranking & LTR: Hands‑on, production‑proven experience implementing modern deep learning ranking architectures—including 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.
• Agentic & AI‑Assisted Development: Proficiency with LLM coding agents and agentic CLI tools (e.g., Claude Code, Gemini) as first‑class tools in the development workflow. Familiarity with the auto‑research paradigm and comfort reviewing large volumes of autonomously generated experiment results.
• 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.
• Problem‑Solving & Ownership: Comfortable navigating ambiguity and translating broad business objectives into well‑scoped data science projects. Hold yourself accountable for outcomes, not just outputs.
• 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

• Hybrid working model: join the team for face‑to‑face collaboration in our Berlin campus 2 days a week.
• 27 days holiday with an extra day on 2nd and 3rd year of service.
• We support your development and career growth opportunities: €1,000 educational budget, language courses, parental support, and access to the Udemy Business platform for online courses.
• Health and fitness: health checkups, meditation, and gym access.
• Financial perks: employee share purchase plan, sabbatical bank, public transportation ticket discount, life & accident insurance, corporate pension plan.
• Food vouchers: digital meal vouchers and food vouchers.
• Relocation support: an article with 10 things to know about moving to Berlin and a relocation hub for more information.

We believe diversity and inclusion are key to creating not only an exciting product, but also an amazing customer and employee experience. We do not discriminate on the basis of race, religion, colour, national origin, gender identity or expression, sexual orientation, age, marital or disability status, or any other characteristic. We encourage you to let us know if you need accommodations or specific accessibility support to ensure a smooth interview experience—just email our Inclusion Officer at [e-mail]. Severely disabled applicants with equal qualifications will be given preferential consideration. You are welcome to share your pronouns (he/she/they) so we can address you respectfully from the start.