The Office of Microsoft’s Chief Economist is seeking a Principal Data Scientist. The Office of the Chief Economist works on a broad range of data-intensive business problems ranging from pricing of complex products to estimating productivity impact of Artificial Intelligence (AI) using observational and experimental data. This opportunity will allow you to develop deep business acumen, apply your expertise to solve business problems with huge monetary impact, and collaborate closely with diverse stakeholders including researchers from different backgrounds.
Responsibilities
As a Principal Data Scientist, you will:
- Review business and product requirements, incorporate research, and provide strategic direction for problem solving.
- Ensure scientific rigor, support the development of methods, and apply your expertise to support business impact.
- Document work and experimentation results and share findings to promote innovation.
- Provide guidance when capturing processes and contribute to ethics and privacy policies related to research processes and data collection.
- Coach engineers in data cleaning and analysis best practices, identify gaps in current data sets, and drive ethics and privacy discussions around data collection and preparation.
- Evaluate your team’s models and recommend improvements as necessary, drive best practices for models, and develop operational models that run at scale.
- Conduct thorough reviews of data analysis and modeling techniques and identify and invent new evaluation methods.
- Research and maintain a deep knowledge of the industry, including trends and technologies, so that you can identify strategy opportunities and contribute to thought leadership & best practices.
- Write extensible code that spans multiple features and develop expertise in proper debugging techniques.
- Define business, customer, and solution strategy goals, and partner with other teams to identify and explore new opportunities.
- Commit to a business-oriented focus by acknowledging their needs and offer pragmatic solutions that align with their data capabilities.
Qualifications
Required/Minimum Qualifications
- 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 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 Doctorate 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.
- 8+ years of technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, or Python.
- 8+ years experience with relational database and SQL skills with working knowledge of data warehousing concepts, including technical architecture, infrastructure components, ETL/ELT and reporting/analytic tools and environments such as Cosmos DB, Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, or Flume.
Additional Or Preferred Qualifications
- Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years 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 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR equivalent experience.
- Previous experience of applying software development skills to economic-oriented problems and deploying statistical models.
Data Science IC5 - The typical base pay range for this role across the U.S. is USD $133,600 - $256,800 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 $173,200 - $282,200 per year.
Certain roles may be eligible for benefits and other compensation.
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.
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