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Microsoft Data Scientist - Multiple Locations 
United States 
260809984

10.09.2024

Required Qualifications:

  • Bachelor's Degree (or currently pursuing) in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
    • OR equivalent experience.

Preferred Qualifications:

  • Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
    • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR equivalent experience.
  • Some Engineering experience and or project course work using large data systems on SQL, Hadoop, etc.
  • Some experience or course work applying basic ML to a type of data and or used algorithms to conduct experiments on data.
  • Proficiency using one or more programming or scripting language to work with data such as: Python, Perl, or C#.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Responsibilities
  • Formulate approaches to solve problems using well defined algorithms and data sources.
  • Incorporate an understanding of product functionality and customer perspective to provide context for those problems.
  • Use data exploration techniques to discover new questions or opportunities within your problem area and propose applicability and limitations of the data.
  • Interpret the results of their analysis, validate their approach, and learn to monitor, analyze, and iterate to continuously improve
  • Engage with peer stakeholders to produce clear, compelling, actionable insights that influence product and service improvements that will impact millions of customers.
  • Participate in the peer review process and act on feedback while learning innovative methods, algorithms, and tools to increase the impact and applicability of your results