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Microsoft’s Cloud Operations & Innovation (CO+I) is the engine that powers our cloud services . As a Principal Data Science Manager, you will perform a key role in delivering the core infrastructure and foundational technologies for Microsoft's online services including Bing, Office 365, Xbox, OneDrive, and the Microsoft Azure platform.

Our infrastructure is comprised of a large global portfolio of more than 200 datacenters in 32 countries and millions of servers. Our foundation is built upon and managed by a team of subject matter experts working to support services for more than 1 billion customers and 20 million businesses in over 90 countries worldwide.

With environmental sustainability and optimization at the forefront of our datacenter design and operations, we continue to grow and evolve as we meet the ever-changing business demands that hold Microsoft as a world-class cloud provider.

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.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Responsibilities

• Lead a team of data scientsts to work on various data science and engineering initiatives across the Cloud Operations and Innovation organization.

• Provide necessary technical leadership driving AI+HI features including but not limited to:

• Data extraction/validation/pipelines

• ML model development & depolyment

• Visualizing analysis and model results

• Collaborate closely with teams across Microsoft to leverage the best technologies, architectures, and ideas to advance the team’s mission.

• Transform ambiguity into clarity for the team. Break down complex projects into workstreams, coordinate execution across several teams & individuals.

• Be an example of great and clean coding, design and overall engineering skills to inspire and educate other team members.​

• Ensure shared understanding of business priorities and implementation plans with the team, partners and key stakeholders.

Qualifications

Required Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ 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 7+ 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 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)

• OR equivalent experience.

• 3+ years people-management experience.

• 5+ years' experience working with technologies such as Spark, Pyspark, Jupyter, MLlib, Linux, Python

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 8+ 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 10+ 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 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)

• OR equivalent experience.

• 5+ years people-management experience.

Data Science M5 - The typical base pay range for this role across the U.S. is USD $133,600 - $256,800 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 $173,200 - $282,200 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

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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) .