Data Scientist - Redmond

Come build community, explore your passions and do your best work at Microsoft. This opportunity will allow you to bring your aspirations, talent, potential - and excitement for the journey ahead.

Data Scientists at Microsoft use machine learning, statistics, experiments, and more to build and improve great products while making business impact. As a Data Scientist you will collaborate with stakeholders, formulate approaches to solve problems and use algorithms and data sources in the context of business and engineering needs. You will also be able to combine your engineering abilities with analytical skills to make customer experiences better. Our Data Scientists use innovative methods, algorithms, and tools daily to drive results throughout Microsoft devices, operating systems, products, and services and provide novel insights into business and customer scenarios.

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.

Please note this application is only for roles based in our Redmond, Washington office. For roles in other offices in the United States, please see our Careers site. 

Required Qualifications:

• Bachelor's Degree (or currently pursuing) in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
  • OR equivalent experience.

Preferred Qualifications:

• Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or  related field AND 1+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience.
• Some Engineering experience and or project course work using large data systems on SQL, Hadoop, etc.
• Some experience or course work applying basic ML to a type of data and or used algorithms to conduct experiments on data.
• Proficiency using one or more programming or scripting language to work with data such as: Python, Perl, or C#.

Data Science IC2 - The typical base pay range for this role across the U.S. is USD $81,900 - $160,200 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 $105,600 - $174,600 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 and processes offers for these roles on an ongoing basis.

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.

• Formulate approaches to solve problems using well defined algorithms and data sources.
• Incorporate an understanding of product functionality and customer perspective to provide context for those problems.
• Use data exploration techniques to discover new questions or opportunities within your problem area and propose applicability and limitations of the data.
• Interpret the results of their analysis, validate their approach, and learn to monitor, analyze, and iterate to continuously improve.
• Engage with peer stakeholders to produce clear, compelling, actionable insights that influence product and service improvements that will impact millions of customers.
• Participate in the peer review process and act on feedback while learning innovative methods, algorithms, and tools to increase the impact and applicability of your results