Designing and training relevance models, including LLM fine-tuning and learning-to-rank (LTR) approaches. Building robust evaluation pipelines using offline metrics and online A/B experimentation. Drive end-to-end applied science projects: From ideation and design to implementation, experimentation, and shipping, you will lead high-impact projects that directly improve Copilot Chat, Copilot Search, and BizChat experiences. This includes identifying search and relevance gaps, formulating innovative hypotheses, and delivering scalable solutions. Innovate with scientific rigor: Invent and apply cutting-edge techniques in machine learning, natural language processing, and information retrieval to address real-world challenges at enterprise scale. You will design novel approaches for improving retrieval, ranking, query understanding, and semantic search in Copilot systems. Document, share, and amplify learnings: Promote a culture of transparency and innovation by capturing experimental results, documenting methodology, and publishing internal learnings. You'll drive knowledge sharing that enables broader impact across the organization. Translate business goals into scientific strategy: Partner closely with product and business stakeholders to align team efforts with high-priority objectives. You will translate ambiguous product requirements into clear, data-driven, and technically feasible directions. Collaborate across organizations and time zones: Work cross-functionally with platform engineering teams, peer science orgs, and product managers to ensure alignment, resolve dependencies, and unblock progress. You'll be a key bridge between applied science innovation and product delivery. Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research) Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. 8+ years of industrial programming experience in modern languages such as Python, Java, C++, or C#, including production-level ML pipelines. Demonstrated expertise in data analysis at scale, including working with logs, telemetry, and large datasets to uncover behavioral patterns, build evaluation datasets, and derive insights. Familiarity with modern machine learning and deep learning frameworks such as PyTorch, TensorFlow, scikit-learn, and Hugging Face Transformers. Proven ability to collaborate across engineering, product, and science organizations and to communicate technical details clearly to both technical and non-technical stakeholders.
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