Microsoft Principal Data & Applied Scientist 

United States, Washington 

382587435

Required/Minimum Qualifications

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ 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, 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 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 equivalent experience.
• 5+ years of experience in machine learning, natural language processing, and deep learning.
• Experience in programming languages such as Python, R, or SQL, with hands-on experience in data analysis, experimental design principles and visualization.
• Experience in translating complex data into actionable insights and recommendations that drive business impact.

Other Requirements

• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. 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 background and Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Additional or Preferred Qualifications

• 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 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 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 equivalent experience.
• Experience in Big Data preferably in the cybersecurity or SaaS industry.
• Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:Microsoft will accept applications for the role August 16, 2024.

• Lead the development and implementation of data-driven strategies to extract actionable insights from telemetry data generated by Copilot for Security.
• Collaborate with product and engineering teams to identify key metrics, design experiments, and evaluate the effectiveness of new features and enhancements.
• Utilize advanced statistical and machine learning techniques to uncover patterns, trends, and correlations within the data, enabling us to better understand customer behavior and preferences.
• Work closely with market analysts to integrate external market trends and intelligence into our data analysis, providing holistic insights that drive informed decision-making.
• Partner with stakeholders to define KPIs and performance metrics, continuously monitoring and optimizing our product performance and user experience.
• Communicate findings and recommendations to leadership and cross-functional teams through compelling visualizations, presentations, and reports.
• Stay abreast of emerging technologies, methodologies, and best practices in data science and analytics, actively contributing to our culture of innovation and excellence.

• Other

  • Embody our