Data Scientist

Would you like to bring your data science skills to work on some of the most impactful problems at Microsoft? The Office of the Chief Economist drives value for Microsoft and its customers by providing insights into some of the most important questions at Microsoft, from the ways that AI will change the way that people work to understanding how efficient pricing can help grow Microsoft’s cloud revenue. The Office of the Chief Economist seeks a Data Scientist with deep knowledge of machine learning and research methodologies, including power analysis, experimental design, hypothesis testing, and inference. 

As a Data Scientist, you will use your expertise in data science, machine learning, and artificial intelligence to drive insights that help Microsoft grow its business through more efficient pricing and decision making.  You will work with business partners to identify areas of the business that can help them drive value, identify data sources and appropriate technique that can deliver critical insights for decision makers, and then develop and execute each step in the analysis work, from data wrangling, quality control and data sleuthing, to producing summary statistics and using statistical and machine learning to deliver statistically sound causal insights to business leaders. 

Our team values collaboration, craftsmanship, and continuous learning. As a member of the team, you will be able to shape and grow a positive and productive data engineering culture.  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. 

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/Minimum 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.
• Deep knowledge of at least one modern statistical programming language, such as R or Python
• Experience with data query languages such as SQL and management platforms such as SQL Server or Cosmos

Additional or Preferred 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)
  • 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.
• Experience with Exploratory Data Analyses, Inference analysis, Predictive analysis (Regression, Classification etc.,) and forecasting. 
• Experience with Experiment Design and analysis. 
• Demonstrated leadership in complex areas, through critical thinking, thought leadership, technical skills and relentless drive for progress.

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.

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.

• Develop a deep understanding of modern and legacy data systems and build data pipelines that enable experimentation and data analysis at scale.
• Understand business needs and develop appropriate data analyses plans to meet those needs ranging from exploratory data analysis, inference and experimentation.
• Sleuth data quality issues that threaten to undermine econometrically sound analysis by identifying clear data requirements and ensuring that analytic datasets meet those rigorous requirements.
• Execute analysis plans ranging from classical statistics to modern machine learning and econometric inference.

Embody our Culture and Values