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Microsoft Data Applied Scientist 
United States, Texas, San Antonio 
501290729

13.08.2024

Required 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.

Other Qualifications:

These requirements include, but are not limited to, the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred Qualifications:

  • Communication and leadership skills to drive projects and build buy-in and support.
  • Demonstrated experience leading and managing a business-critical function.
  • Technical certifications relevant to data analysis/BI


Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:Microsoft will accept applications for the role until Aug 15, 2024.


Responsibilities
  • Apply their expertise in quantitative analysis, data mining, and the presentation of data to develop econometric/ ML models.
  • Connect and build APIs for turning data science models into a full production system.
  • Understand fundamental business dynamics impacting demand and develop automated statistical solutions for forecasting.
  • Develop E2E models in R/ Python – including data manipulation, model building and business applications.
  • Collaborate with cross-functional teams to understand business needs and identify opportunities for leveraging company data to drive business solutions.