Senior Data Scientist - Microsoft Azure

Get ready to operate at hyperscale!

We are building new systems to optimize the millions of server nodes underlying the Microsoft Azure cloud. You will be part of a dynamic and collaborative team chartered to understand and improve how hardware and software ingredients come together to form our Azure virtual machine (VM) products. Our work includes fleet optimization, server health/performance testing, representative benchmark construction, competitive comparisons, customer collaborations, server platform definition, and more.

As a Senior Data Scientist - Microsoft Azure in this role, you will craft sampling experiments and perform analysis to characterize the behavior of Azure's mainstream server fleet. You will define sound approaches, based on statistical inference, to assess fleet health and performance, assess similarity between customer workloads and internal proxies, detect server behavior anomalies using telemetry, and more. Based on the understanding you create, you will partner with software engineers and machine learning engineers to improve Azure products and customer experiences. Along the way, you will gain experience in hyperscale cloud computing, a fast-moving industry that permeates nearly every aspect of modern life. Our team is based in Redmond, WA. This is a hybrid work opportunity and you have the option to work remotely.

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:

• 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.

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

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    OR Master'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)

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    OR Bachelor'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))

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    OR equivalent experience.

• 2+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.
• Experience with Kusto, Python, and R.
• Experience within the computing industry.

Data Science IC4 - The typical base pay range for this role across the U.S. is USD $117,200 - $229,200 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 $153,600 - $250,200 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   

Microsoft will accept applications for the role until June 6, 2024. 

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.

#azurecorejobs

• Define experimental methodology for assessing health and performance consistency across a fleet of millions of server nodes.
• Select benchmarks through statistical methods that achieve both representativeness and coverage of workload behavior based on collected telemetry.
• Create anomaly detection methodologies, both online and offline, for identifying problematic server hardware or configurations.
• Identify opportunities to improve operational efficiency and customer experience through statistical and predictive models.
• Create dashboards, data views, and reports based on your experiments and analysis.

Other

•  Embody our Culture  &  Values