Microsoft’s Cloud business is expanding, and the Cloud Supply Chain (CSCP) organization is responsible for enabling the infrastructure underlying this growth including AI! CSCP’s vision is to empower customers to achieve more by delivering Cloud Capacity Differentiated at Scale. Our mission is to deliver capacity for all cloud services predictably through intelligent systems driven by continuous learning and a world class organization. The CSCP Organization is responsible for traditional supply chain functions such as Plan, Source, Make, Deliver, but also manages supportability (spares), decommissioning and disposition of Data center assets worldwide. We deliver the core infrastructure and foundational technologies for Microsoft's over 200 online businesses including Bing, MSN, Office 365, Xbox Live, Skype, OneDrive and the Microsoft Azure platform for external customers. Our infrastructure is comprised of a large global portfolio of more than 200 datacenters supporting services for more than 1 billion customers in over 90 countries worldwide.
The Capacity, Supply Chain & Provisioning Engineering (CSCP-E) group is an exciting and fast evolving engineering group within Microsoft that powers Microsoft’s Cloud-First mission. We are responsible for supporting the supply chain that powers Microsoft Azure’s cloud infrastructure. This is a great opportunity to join a dynamic team and influence the way one of the world’s largest and fastest growing cloud environments is built and supported. We are looking for a Senior Data Scientist Manager to help us with a new project that has a lot of impact and visibility. The best fit candidate will lead the team that will blend Data Science and Software engineering skills, with an ability to work across teams to build successful solution for a diverse set of stakeholders. You will also collaborate with various engineering teams to explore new applications of AI research areas and implement architectural changes.
Lead and manage a team of Data Scientists driving the development and implementation of cutting-edge AI / ML technologies. Work with business leaders, engineering leaders, researchers and other data scientists to formulate data-driven answers to hard business and decision-making problems, applying a wide variety of data and techniques to help drive the engineering investments at a strategic and tactical level. Convert complex design into solid implementations that scale and perform Oversees the analysis of data and leads the team in identifying trends, patterns, correlations, and insights to develop new forecasting models and improve existing models. Ensure solution delivered adheres to the technological standards established in the organization Lead from the front by diving into individual problem areas and guide the team by making recommendations and best approaches. Set up best practices, standards and guidelines. Work closely with a variety of teams like data science, engineering and PM teams. Drive the development of Machine Learning models and solutions using classical algorithms as well as foundation models. Embody our Culture and Values.
Minimum Qualifications
Preferred Qualifications
Excellent collaboration and communication skills to work effectively with cross-functional teams Strong problem-solving abilities and a strategic mindset to drive innovation and achieve business goals.
Experience with AI product integration and deployment in real-world scenarios.
Familiarity with Microsoft technologies and platforms like Azure ML Ops, Azure AI Studio, Copilot Studio etc is a big plus.
Prior experience in machine learning using R or Python (scikit / numpy / pandas / statsmodel).
Prior experience in time series forecasting.
Prior experience with typical data management systems and tools such as SQL.
Knowledge and ability to work within a large-scale computing or big data context, and hands-on experience with Hadoop, Spark, Synapse/DataBricks or similar.
Excellent analytical skills; ability to understand business needs and translate them into technical solutions, including analysis specifications and models.
Advanced degree (Ph.D. or equivalent) in Computer Science, Engineering, or a related field is preferred.
PhD in Statistics, Applied Mathematics, Applied Economics, Computer Science or Engineering, Data Science, Operations
Research or similar applied quantitative field.
Experience with deep learning models (e.g., tensorflow, PyTorch, CNTK) and solid knowledge of theory and practice.
Practical and professional experience contributing to and maintaining a large code base with code versioning systems such as Git.
Knowledge of supply chain models, Demand forecasting etc. will be a big plus.
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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.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.
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