Data Scientist

at  Microsoft

It’s an exciting time to join Microsoft! The Office of the Chief Economist works across the company to pursue commercial value using economic and data-driven thinking. Some examples of our work include algorithms that grow Microsoft’s cloud revenue as well as its resource efficiency, some of the first-ever studies of how AI changes the way that people work, and business model analytics for our software licensing models.
We are looking for a Data Scientist with broad technical skills, business acumen, and an entrepreneurial spirit. You will work alongside world-class colleagues on high-visibility projects answering some of Microsoft’s most pressing challenges. You will work directly with business partners to identify business opportunities, you will discover enormous new datasets for analysis, and you will sleuth the data and its business implications. You will use statistics and machine learning to deliver statistically sound causal insights to business leaders.
Successful candidates can dive deep into sophisticated modeling approaches when needed; but more importantly, they know when a simple and pragmatic solution will do just as well. They know how to tell good stories through data, how to visualize, and how to use many fast iterations in the face of ambiguous problems. Great candidates thrive in an environment that promotes learning through diverse projects.
Our team values collaboration, craftsmanship, and continuous learning. 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. We value 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.
Relocation assistance is unavailable for this role.

REQUIRED/MINIMUM QUALIFICATIONS

• Doctorate in Data Science, Computer Science, Electrical Engineering, Mathematics, Economics, Operations Research, or related field
• OR Master’s Degree in Data Science, Computer Science, Electrical Engineering, Mathematics, Economics, Operations Research, 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, Computer Science, Electrical Engineering, Mathematics, Economics, Operations Research, 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, Computer Science, Electrical Engineering, Mathematics, Economics, Operations Research, 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, Computer Science, Electrical Engineering, Mathematics, Economics, Operations Research, 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, Computer Science, Electrical Engineering, Mathematics, Economics, Operations Research, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)o OR equivalent experience
• Experience building data pipelines, including automated data quality checking.
• Experience with Exploratory Data Analyses, inference analysis, predictive analysis (Regression, Classification etc.,) and forecasting.
• Experience with experiment design and analysis.
• Experience with modern data infrastructure, such as Spark, cloud services, or Databricks.
• Demonstrated experience using visualization to explain business insights from data.
• Effective communication skills with a broad range of audiences and ability to influence without authority.
  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
  Single reqs: Microsoft will accept applications for the role until December 1, 2024.
  Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations

• 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 to meet those needs ranging from exploratory data analysis, inference, and experimentation.
• Investigate data quality issues that threaten to undermine econometrically sound analysis by identifying clear data requirements.
• Together with your team, interpret and present findings to stakeholders.
  Embody our Culture and Values