Senior Data Scientist - (Global Search, Consumer)

Job DescriptionWe 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. Your mission: 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. You will 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. You will leverage LLM coding agents (e.g., Claude Code, Gemini) to autonomously iterate on feature engineering and Learning to Rank (LTR) architectures. Inspired by the auto-research paradigm, you will design overnight experiment pipelines and review the outputs of hundreds of autonomous runs to identify signals quickly.Lead Feature Engineering and Model Architecture Innovation: 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.Ensure Production Reliability: Maintain rigorous standards for model health in production. You will 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.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 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.