Join the forefront of sustainable innovation at Microsoft's Cloud Operations & Innovation (CO+I) as a Critical Environment Data Scientist II. In this pivotal role, you'll be instrumental in driving the sustainable evolution of our core infrastructure and foundational technologies that power Microsoft's leading online services, including Bing, Office 365, Xbox, OneDrive, and the Microsoft Azure platform.

Imagine harnessing the power of machine learning models, big data, and predictive analytics to transform the landscape of data center sustainability. With over 200 data centers spanning 32 countries and millions of servers, our global infrastructure is a playground for ambitious data scientists eager to make a tangible impact. Collaborating with a team of experts, you'll support services for over 1 billion customers and 20 million businesses across 90 countries, pushing the boundaries of what's possible in the world of cloud computing. 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.

+ 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 will need to relocate or reside within 50 miles of the hub office location.

+ This role is eligible for hybrid or remote work, up to 100%.

**Responsibilities**

+ Leverage advancements in Data Science, Machine Learning, and AI to support sustainability objectives and enhance efficiency in data center operations.

+ Assist in translating complex data into actionable insights and presenting findings to stakeholders.

+ Collaborate on the design and execution of experiments to test hypotheses and evaluate new approaches, ensuring the reliability and validity of results.

+ Contribute feedback to the engineering team regarding potential business opportunities and product enhancements based on data analysis and findings.

Embody our Culture (https://www.microsoft.com/en-us/about/corporate-values) and Values (https://careers.microsoft.com/us/en/culture)

**Qualifications**

**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 techniques and reporting results) or consulting experience

+ 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 techniques and reporting results)

+ OR equivalent experience.

+ 2+ years of experience working in a role as a data scientist

+ Experience in working with software engineering teams, hardware engineering teams, and data science teams.

**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:**

+ Experience with large-scale product and service telemetry systems, demonstrating a deep understanding of data collection, processing, and analysis methodologies.

+ Experience with Exploratory Data Analyses, Inference analysis, Predictive analysis (Regression, Classification etc.) and forecasting.

+ Solid foundation in applied statistics and mathematics, with the ability to apply advanced analytical techniques to solve complex problems.

+ Experience with a analytical programming languages such as Python.

Data Science IC3 - The typical base pay range for this role across the U.S. is USD $98,300 - $193,200 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 $127,200 - $208,800 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 2, 2024.

\#COICareers

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) .