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Are you a real Machine Learning enthusiast? Does the magic of the data world fascinate you? Here at Microsoft Search we have been working on Machine Learning much before it became cool to do so. Here we are solving real world problems to empower millions of people around the globe. Microsoft Search powers delightful and relevant experiences for enterprise users to cater to their overall information need. As part of this team, you would get a chance to work on the core search stack powering all Copilot Search scenarios. We’re looking for an Data Scientist II with deep expertise in applied AI and a strong track record of delivering products built using ML models at scale. The candidate should have hands on experiences with building machine learning models over large scale data. Experience with latest advancements in embedding models is preferred. This is a unique opportunity to build the next generation search stack in Microsoft. You’ll join a fast-paced, collaborative environment that brings together talent from across Microsoft—including Microsoft Research—to push the boundaries of what’s possible with State of the Art Embedding Models, Cross Encoder Models, Deep Neural Nets as well as classical GradientBoostedTree (GBT) models.
Job Responsibility:
Advance the science: Design and run experiments, define and validate metrics, and develop ML pipelines and models in areas like encoder-decoder models, cross-encoder models
Working with Language models to understand user intent and developing a semantic search stack optimizing for the various search intents
Working with large scale data and derive insights out of it while championing Privacy and Compliance
Drive product innovation: Partner with Engineering, PM, and Design to translate product vision and industry trends into scalable, reliable, and agile architecture
Collaborate across Microsoft: Work closely with Microsoft Research, Azure, AI platform teams, and product groups to bring cutting-edge AI into real-world applications
Champion customer impact: Engage with customers and internal teams to deeply understand pain points and drive improvements that matter
Define success: Measure success metrics that reflect platform and product growth
Stay ahead: Keep up with the latest research and foster a thriving applied science culture
Requirements:
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience
OR equivalent experience
1+ years of Python coding skill
Ability to meet Microsoft, customer and/or government security screening requirements
Microsoft Cloud Background Check
Nice to have:
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience
OR equivalent experience
Experience with latest advancements in embedding models
Hands on experiences with building machine learning models over large scale data