Applied Scientist

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Are you passionate about Cloud Computing technology and driving growth in one of Microsoft’s core businesses? Do you aspire to be part of a team relentlessly focused on customer needs, market expansion, and advancing Microsoft Cloud’s first strategy? If yes, look no further than Microsoft Cloud Operations + Innovation (CO+I).

CO+I is the engine that powers Microsoft's cloud services. CO+I is responsible for designing, building, and operating our unified global datacenters, managing the supply planning and capacity utilization of our unified infrastructure, and is responsible for all operations needed to run the physical infrastructure including supply chain, hardware, power, security, and workflow teams.

We are seeking an Applied Scientist with strong data and software engineering expertise. Our team develops long-range capacity plans for Azure datacenters by leveraging advanced demand forecasting models, business strategies, and a wide array of data sources. In this role, you will be responsible for enhancing and maintaining our demand planning engine, designing robust data pipelines to integrate diverse datasets, and generating scalable capacity plans aligned with evolving business needs. You will also support the Secure Future Initiative (SFI)—Microsoft’s company-wide effort to proactively identify and remediate security vulnerabilities—by ensuring our planning systems and data workflows meet the highest standards of security and resilience.

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.

Required Qualifications:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND relevant internship experience (e.g., statistics, predictive analytics, research)
  • OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
  • OR equivalent experience.
• 2+ years' experience in applications of computer science, advanced statistical, analytical techniques or equivalent experience.
• 2+ years' experience with coding in languages including C, C++, C#, Java, JavaScript, or Python.
• Experience in SQL and/or NO-SQL databases.

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:

• Excellent communication and leadership skills to drive projects and build buy-in and support.
• Demonstrated experience leading and managing a business-critical function.
• Technical certifications relevant to data analysis/BI.

Applied Sciences IC2 - The typical base pay range for this role across the U.S. is USD $84,200 - $165,200 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 $109,000 - $180,400 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 11/18/2025.

#COICareers | #EPCCareers | #DCDCareers

• Build and maintain ADO pipelines, and maintain Azure Assets (subscription, blob storage, SQL database, key vault, etc.) in a secure and compliant manner.
• Connect to and build APIs for turning data science models into a full production system.
• Develop and productionize E2E models in Python – including data manipulation, model building, and business applications.
• Apply expertise in quantitative analysis, data mining, and the presentation of data to develop demand forecasting models.