Senior Data Scientist

Microsoft’s Experimentation Platform (ExP) is a team within Microsoft's AI Platform team in Azure and we empower product teams across Microsoft to innovate and make data-driven decisions through trustworthy experimentation at scale. This includes many multi-billion-dollar businesses such as Bing, Office, Azure, MS (Microsoft) Teams, MSN, Xbox, Windows, and more. We have been researching, developing, and operating ExP for over 17 years and have most recently evolved our offering into an Azure service. The goal of our Azure stack is to accelerate innovations for key partners across Microsoft by enabling testing of innovative ideas quickly and reliably. This includes: What factors affect the quality of the Bing user experience? What causes users to make their first payment with XBox? The list of needs grows every day especially with the company-wide focus on AI.  

In this role you will directly contribute to building Microsoft’s experimentation platform, one of the largest A/B testing platforms on the planet. As a part of the Azure ExP team, you will get the opportunity to push the envelope for how data is leveraged and change the way software is built across Microsoft. This includes working with a world-class PM team, collaborating with agile engineering teams and leveraging the statistical expertise of our data scientists.  

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.

Required/Minimum 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.

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)
  • 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)
  • 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)
  • OR equivalent experience.
• Bachelor's or Master's degree in a quantitative field, and at least 5 years of relevant work experience. PhD preferred. 
• Strong programming skills - We are programming-language agnostic so welcome all languages but prefer Java, C++, C# with tools such as Hadoop, Spark, Pig or Hive in your background.
• Scripting knowledge in Python, R, MATLAB, Perl, SQL or similar languages.
• Superior verbal, visual and written communication skills to educate and work with cross functional teams on controlled experiments.

Data Sciences 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 October 31, 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.

#aiplatform 

• Apply your expertise in quantitative analysis, data mining, and the presentation of data to develop experiments and provide algorithmic problem-solving solutions. 

• Build data manipulation, processing, and data visualization tools and share these tools and your knowledge across the team, and Microsoft. 

• Handle large amounts of data using various tools, including your own.  

• Ensure high-quality data and understand how that data which is generated out experimental design can produce actionable, trustworthy conclusions. 

• Partner with internal clients such as Xbox, Windows, Skype for Business, Teams, Microsoft Office 365  

• Drive end-to-end projects by utilizing, applying and analyzing data associated business problems. 

• Engage with senior management in making key business decisions. 

• Mentor others in the team.