Data Scientist II

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Azure is Microsoft’s central cloud infrastructure, hosting both public cloud offerings and a wide range of internal, cloud-scale services. Cloud computing is a rapidly growing market, and Azure aims to be an industry leader across all relevant dimensions of its platform and services. Within Azure, the Azure Compute team serves as the core infrastructure group responsible for hosting virtual machines (VMs), containers, and other workloads. Are you interested in working in an exciting cloud computing space where you build data-driven systems, are part of a supportive team that encourages new ideas and innovation, and where your work has a significant impact across Microsoft Azure and the enterprise services built on it? If so, this position may be the right fit for you.

One of the foundational disciplines in cloud computing is capacity management. This discipline ensures that there is sufficient capacity across all regions, allocation domains, and hardware infrastructure to meet customer demand, while also provisioning that capacity efficiently to avoid overspending and negative impacts on Cost of Goods Sold (COGS) and Capital Expenditures (CAPEX). At Azure’s scale, managing this trade-off across the entire Azure Compute fleet is a highly complex problems—where improvements can mean the difference between customer allocation failures and massive cost savings. The Azure Compute Capacity and Efficiency (AC2E) team is responsible for managing all aspects of capacity and efficiency across the fleet. Our primary mission is to deliver a fully automated and highly optimized tracking and management system. A core component of this system is the Capacity Management Automation System (CMAS), which leverages advanced algorithms and artificial intelligence (AI) to predict capacity risks and automatically execute mitigation actions within the Azure Compute platform.

As a Data Scientist on this team, your work will directly contribute to improvements in the Azure platform, fulfillment rates for Azure services, customer satisfaction, and efficiency metrics—including reductions in Cost of Goods Sold (COGS). Our team is a balanced mix of data scientists and development engineers, working closely with program managers. We apply state-of-the-art data science and statistical techniques such as anomaly detection, machine learning (ML), and experimentation methodologies. If you are passionate about applying these techniques to solve complex, real-world problems, you will thrive in our team. Together, we deliver world-class innovation.

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

Required Qualifications:

• 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 tec
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical tec
  • OR equivalent experience.
• 1+ year(s) experience with python or R.

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:

• Doctorate 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 Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science,
  • OR related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Bachelor's Degree 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 equivalent experience.
• Familiarity with Azure is a plus.

Data Science IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $131,400 - $215,400 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft will accept applications for the role until July 18, 2025.

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• Help with initial data collection and understand which analysis techniques are appropriate and which tools are necessary for data exploration. You’ll also develop a foundational understanding of methodology and standard statistical options so that you can analyze and organize data as required.
• You will understand modeling techniques used within the team, then run model tools on prepared data sets. You’ll also analyze model performance and incorporate customer feedback into its evaluation.
• Understand the current state of the industry, including current trend. You’ll also write code for a specific feature or model and develop an understanding of proper debugging techniques.
• Understand each customer’s business goals and learn how to identify growth opportunities. You’ll also examine projects through a customer-oriented focus and manage customer expectations regarding project progress.
• Develop Data insights, analysis, recommendations generation gaining deeper domain knowledge.
• Integrate analytics intelligence, ML capabilities into the Azure platform.
• Collaborate with Microsoft Researchers on strategic projects as applicable.
• Embody our Culture and Values.