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Microsoft Principal Data & Applied Scientist 
United States, Washington 
349598204

17.12.2024


Required Qualifications:

  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
    • OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research)
    • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
    • OR equivalent experience.
  • 4+ years experiencein Python.
  • 4+ years experience in designing and implementing search engine metrics, preferably with projects that involve LLMs.

Preferred Qualifications:

  • 5+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.
  • Understanding of traditional search engine metrics like precision, recall, Mean Reciprocal Rank (MRR), and Normalized Discounted Cumulative Gain (NDCG)
  • Customer focused, strategic, drives for results, is self-motivated, and has a propensity for action.

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 December 17, 2024.


Responsibilities
  • Define, invent, and deliver behavioral and human labeled metrics which accurately measure the satisfaction and success of our customers.
  • Research, analyze, and decide between various sampling strategies which accurately reflect user perception.
  • Lead a team to design a blueprint for how to get high quality labels with latest technologies and expert judges.
  • Enable other machine learning scientists in the broader group to experiment quickly and accurately.
  • 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.
  • Partner effectively with program management, engineers, and other areas of the business.