Senior Data Scientist - Global Search and Consumer Experience

About Delivery Hero

Delivery Hero is a leading local delivery platform operating across approximately 65 countries with a mission to provide fast, effortless delivery experiences. Headquartered in Berlin, Germany, the company is publicly traded on the Frankfurt Stock Exchange and is a member of the MDAX index. Our platform supports millions daily and fosters innovation through technology.

Role Overview

We are seeking a Senior Data Scientist to join our Global Search tribe, particularly within the Search Ranking team. This role focuses on creating and deploying sophisticated deep learning ranking models for search results that influence over 80 million queries each day across more than 60 countries and 35 languages. The position involves pioneering autonomous AI-driven experimentation and optimizing search relevance.

Key Responsibilities

• Take complete ownership of the ranking stack by designing, implementing, and scaling deep neural ranking models such as DCN-V2, MMoE, and Two-Tower architectures to perform efficiently at scale with low latency.
• Champion agentic machine learning research by utilizing large language model coding agents like Claude Code and Gemini to autonomously conduct feature engineering and experiment orchestration, overseeing extensive autonomous experiment results to extract valuable insights quickly.
• Innovate and enhance ranking systems by applying expertise in ranking signals, feature stores, and embedding-based retrieval, translating academic advances into high-quality production systems.
• Maintain high production standards by monitoring model drift, response latency, and feature pipeline health to ensure consistent and reliable ranking quality globally.
• Collaborate effectively with backend engineers, data engineers, and product managers to achieve comprehensive improvements and communicate complex ML concepts and trade-offs clearly to stakeholders.
• Mentor junior and mid-level data scientists, advocate for rigorous experimentation and clean code practices, and promote a culture of continuous learning focused on emerging agentic development methodologies.

Qualifications

• Master's degree in Computer Science, Mathematics, Physics, or a related quantitative field, or a Bachelor's degree with over six years of relevant professional experience.
• At least four years of professional experience as a Data Scientist or Machine Learning Engineer applying ML techniques in high-traffic production environments.
• Proven expertise in deep learning ranking and Learning to Rank (LTR) methodologies, including architectures such as DCN-V2, MMoE, and Two-Tower, mastery of multi-task learning and embedding optimization, and familiarity with offline evaluation metrics like NDCG and MRR.
• Experienced with agentic and AI-assisted development workflows using LLM coding agents for autonomous experiment generation and rapid prototyping.
• Strong technical proficiency in Python and ML frameworks including PyTorch, TensorFlow, and scikit-learn; skilled with SQL (dbt), cloud platforms like GCP or AWS, and big data tools such as PySpark and Scala.
• Comprehensive knowledge of the ML lifecycle including feature stores, vector databases, experiment tracking, model versioning, and deployment practices essential for low-latency high-throughput serving.
• Proven problem-solving ability, accountability for results, and capability to navigate ambiguity while translating business goals into actionable data science projects.
• Excellent communication and teamwork skills to collaborate within diverse, globally distributed teams and convey complex technical matters to non-specialists.

Additional Information and Benefits

• Hybrid work arrangement with mandatory two days per week onsite at our Berlin campus for team collaboration.
• 27 days of annual leave with an additional day granted in the second and third years of service.
• Generous professional development support including €1,000 educational budget, language classes, parental support, and access to Udemy Business for online learning.
• Wellness benefits such as health checkups, meditation sessions, and gym facilities.
• Financial benefits including Employee Share Purchase Plans, Sabbatical Bank, discounted public transit passes, life and accident insurance, and corporate pension schemes.
• Food perks including digital meal and food vouchers to foster connection through shared meals.
• Relocation support and resources to assist new hires in moving to Berlin.
• Inclusive hiring practices promoting diversity, equity, and accessibility, with accommodations available during the interview process upon request.
• Special preference given to equally qualified candidates with severe disabilities.
• Encouragement to share personal pronouns to ensure respectful communication from the outset.