Senior Data Scientist — (Global Search, Consumer)

Описание

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

• 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.
• 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 (LTR) architectures.
• Design overnight experiment pipelines and review the outputs of hundreds of autonomous runs to identify signals quickly.
• 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.
• 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 — keeping our ranking quality high for users across all markets.
• 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.
• 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.

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 the challenges of bridging offline metrics to online A/B outcomes.
• 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.
• 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.
• Comfortable navigating ambiguity and translating broad business objectives into well-scoped data science projects.
• 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.

We offer

• Hybrid working model: join the team for face-to-face connection and collaboration in our beautiful Berlin campus 2 days a week.
• 27 days holiday with an extra day on 2nd and 3rd year of service.
• 1.000 € Educational Budget, Language Courses, Parental Support and access to the 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 and Food Vouchers.

Hiring process

• 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 •••.
• 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.