Cloud Operations and Innovation (CO+I) is the engine behind Azure and the Microsoft Cloud. The CO+I organization delivers and operates the safest, most available, and secure cloud in the industry. In support of this mission, the Cloud Applied AI (CAAI) team works to infuse machine learning, statistical analysis, operations research, econometrics, and generative AI throughout every facet of the organization.

We are seeking a Prinicipal Data Science Manager to with a background in research and data science with experience leading teams of data and applied scientists. This leader will partner with software engineering and business leaders across the organization to develop cutting-edge models that seamlessly integrate with the large-scale distributed systems powering Microsoft’s cloud infrastructure.

This leader will guide a diverse team of data scientists working on a broad portfolio of initiatives, including:

Datacenter construction
Safety & security
Delivery planning & execution
Infrastructure optimization
Critical operations

This individual will leverage their experience in data science while staying abreast of the latest research and developments to identify innovative approaches to solving challenges at scale. This leader will collaborate with engineering and product counterparts to deploy these solutions in production environments supporting Microsoft’s datacenters globally.

This role is located either in one or all hub locations - Atlanta, GA, Washington, D.C., Redmond, WA, San Antonio, TX or Phoenix, AZ.
Relocation support will be provided, and successful candidates must relocate or reside within 50 miles of the hub office location.
This role is eligible for hybrid or remote work, up to (XX indicated by HM)%.

Required/Minimum Qualifications

Bachelors Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
- OR Masters Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
3+ years people management experience.
8+ years of experience in data science developing and deploying models and solutions with a focus on data platforms, machine learning, and analytics
- OR equivalent experience.

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.

Additional or Preferred Qualifications

Masters Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 12+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience.
7+ years people management experience.
3+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
7+ years experience conducting research as part of a research program (in academic or industry settings).
5+ years experience developing and deploying live production systems, as part of a product team.
7+ years experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.
Experience in datacenter operations, manufacturing, or similar operational environments.
Experience leveraging generative AI to optimize processes or enhance software systems

Applied Sciences M6 - The typical base pay range for this role across the U.S. is USD $161,600 - $286,200 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 $209,600 - $314,400 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 March 12, 2025.

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. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. 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.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

## COICareers | ## EPCCareers | ## DCDCareers

Lead and manage the data science team, ensuring the delivery of high-quality data science models and solutions.
Collaborate with senior leaders to define and execute the data science strategy.
Develop and implement data science models that measurably contribute to organizational goals.
Work closely with cross-functional teams to identify and prioritize data science projects.
Drive continuous improvement in data science processes and methodologies.
Mentor and develop team members, fostering a culture of innovation and excellence.
Stay current with the latest advancements in data science and machine learning, and apply them to solve business problems.
Hire, retain, and develop top talent, ensuring the team has the skills and expertise needed to meet current and future challenges.
Promote diversity and inclusion within the team, creating an environment where all team members feel valued and supported.