Principal Data Scientist
Microsoft
Principal Data Scientist
Redmond, Washington, United States
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Overview
We are looking for Principal Data Scientist who are willing to work in a dynamic environment to solve real life day to day problems, leveraging data science techniques. You will enjoy and be successful in this role if you are curious and willing to challenge the status quo and come up with data driven solutions to ambiguous problems.
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.
Qualifications
Required Qualifications:
- Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ 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 7+ 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 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR equivalent experience.
- OR Master'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)
- Experience in at least one of programming languages like Python/R/MATLAB/C#/Java/C++.
Preferred Qualifications:
- 15+ years data-science experience in managing structured and unstructured data, applying statistical techniques and reporting results
- Experience with marketplace evaluation and experimenation
- Experience with driving large collaboration across multiple teams.
- Experience with communicating with different audiences to provide insights.
Data Science IC5 - The typical base pay range for this role across the U.S. is USD $137,600 - $267,000 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 $180,400 - $294,000 per year.
Data Science IC6 - The typical base pay range for this role across the U.S. is USD $161,600 - $286,200 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 $209,600 - $314,400 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.
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Responsibilities
- Measurement: Define, invent, and deliver metrics which accurately measure user and business value across various products and marketplace components.
- Experimental Design: Think critically about sampling and experimental design across User and Demand dimensions.
- Product Iteration: Interpret the results of analyses, validate approaches, and learn to monitor, analyze, and iterate to continuously improve.
- Cooperation: Partner effectively with program management, engineers, and other areas of the business across our Consumer online business.
- Influence: engage with stakeholders to produce clear, compelling, and actionable insights and data-science driven workflows that influence product and service improvements.
- Make independent decisions for the team and handle difficult tradeoffs.
- Translate strategy into plans that are clear and measurable, with progress shared out monthly to stakeholders.