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Microsoft Corporation Principal Data Scientist - Time + Places in Suzhou, China

The Time + Places team is dedicated to reimagining when, where, and how work happens by driving innovation in two key products in the Microsoft 365 suite: Microsoft Calendar and Microsoft Places. Our goal is to create a thriving world by helping users manage their time, stay productive, and thrive whether they're working in an office, from home, or somewhere in between. 

Microsoft Calendar enables users around the world to manage their time more effectively across work and life by offering intelligent solutions for scheduling, meeting collaboration, and task management. 

Microsoft Places is a cutting-edge solution designed to help organizations adapt to the evolving needs of hybrid work. It coordinates where work happens, modernizes workplaces with intelligent technology, and optimizes the workplace for the future. 

As a Principal Data & Applied Scientist, you will play a key role in shaping the future of these products. Working with vast amounts of data, cutting-edge large language models (LLMs) like GPT-4, and modern machine learning (ML) techniques, you will develop the next generation of intelligent solutions for meeting scheduling, relevance, and hybrid workplace collaboration. 

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. 

Responsibilities

  • Machine Learning Innovation: Lead the development of advanced machine learning models that address user needs in time management and hybrid work settings. Use LLMs and other data sources (meeting data, documents, and emails) to create solutions for meeting prioritization, scheduling, and feature quality evaluations. 

  • Relevance & Personalization Models: Architect and refine both supervised and unsupervised models that optimize the relevance of key features within Microsoft Calendar and Microsoft Places. Improve meeting scheduling and hybrid work experiences by extracting meaningful signals from meeting titles, agendas, documents, and participants. 

  • Collaborate on Product Development: Partner closely with product and engineering teams to translate user needs into actionable machine learning solutions. Ensure models are effectively integrated into products, meeting scalability, quality, and real-time performance requirements. 

  • Utilize Industry-Leading Tools: Access Microsoft’s vast data scale, computing resources, and advanced machine learning frameworks to deliver high-impact solutions. Apply prompt optimization, fine-tuning, and retrieval-augmented generation (RAG) techniques to ensure models deliver optimal results. 

  • Performance Metrics: Define, track, and refine key performance metrics for machine learning models. Continuously iterate on models based on user feedback and real-time data to improve accuracy, precision, and recall. 

Qualifications

Required Qualifications:

  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)

  • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience

  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience

  • OR equivalent experience.

  • 5+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.

  • Expertise in Python, SQL, Databricks, Azure ML, Spark, and experience with large language models (LLMs), supervised/unsupervised learning, and natural language processing (NLP). 

  • Experience in architecting and integrating machine learning models into customer-facing products, with a focus on optimizing relevance, personalization, and user engagement. 

Other Requirements:

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:

  • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred Qualifications:

  • Ability to lead technical efforts and collaborate effectively with cross-functional teams (product, engineering). Strong communication skills to present complex data science insights to both technical and non-technical stakeholders. 

  • Experience with workplace productivity tools, scheduling systems, or hybrid work solutions. 

  • Familiarity with real-time data feedback loops and experience optimizing models based on user feedback.  

  • Expertise in fine-tuning LLMs and implementing RAG techniques to improve model performance. 

  • Prior working experience with Enterprise products. 

#M365CORE

Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations (https://careers.microsoft.com/v2/global/en/accessibility.html) .

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