Data Scientist: Opportunities - PhD - Redmond

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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: Opportunities - PhD - Redmond 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:

• Doctorate (or currently pursuing) in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field.

Preferred Qualifications:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
  • OR equivalent experience.
• 1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).
• Experience or course work applying 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 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 and processes offers for these roles on an ongoing basis.

• Formulate and execute problem-solving strategies using well-defined algorithms and comprehensive data sources, ensuring alignment with project goals and business impact.
• Incorporate a deep understanding of product functionality and customer perspective to contextualize problems and enhance the relevance of solutions.
• Utilize data exploration techniques to uncover new questions or opportunities, assessing the applicability and limitations of data to drive innovation.
• Analyze results, validate analytical approaches, and employ monitoring techniques to iterate and continuously improve processes and outcomes.
• Engage with peers and stakeholders to generate clear, compelling insights that influence product and service improvements, impacting millions of customers.
• Actively participate in the peer review process, incorporating feedback and learning innovative methods, algorithms, and tools to enhance the impact and applicability of results

Embody our Culture and Values