Microsoft Principal Data Scientist 

United States, Washington 

844508040

Experimentation & Insights

Principal Data Scientisttrustworthy, data-driven decision-making by delivering actionable insights from data analysis.

Required/Minimum Qualifications

• 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 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
  • 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, etc.)
  • OR equivalent experience.
• 5+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.

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 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, orrelated 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, orrelated 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.
• Domain Expertise: Experience in AI product evaluation, experimentation platforms, or decision science within a tech-driven organization.
• Communication Skills: Strong ability to translate complex data insights into actionable business recommendations for non-technical audiences.
• Proficiency in Statistical Methods: Strong understanding of hypothesis testing, causal inference and techniques like regression analysis and Bayesian inference.
• Expertise in Experimentation: Hands-on experience with A/B testing, multi-armed bandits, causal inference, and other advanced experimentation methodologies.
• Experience with Large-Scale Data Systems: Familiarity with big data technologies such as Spark, Hadoop, Databricks, or Azure Synapse Analytics.
• Coding and Automation Skills: Experience with building reusable data pipelines, automation scripts, and working with version control systems (e.g., Git).
• Experience publishing or presenting work in industry conferences.

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 January 31, 2025.

a PrincipalData Scientist on our team, your responsibilities will include:

• Partner with engineering, product, and leadership teams to implement scalable data-driven frameworks for evaluating AI services and products.

• Drive the design and execution of experiments that ensure reliable insights for business impact.

• Develop and advocate for best practices in A/B testing, causal inference, and evaluation strategies.

• Build tools for data manipulation, processing, and visualization to extract insights and share these tools, knowledge, and findings across partner teams.

• Influence decision-making by providing clarity through complex datasets and statistical analyses.
• Mentor and guide data scientists across the organization, fostering a culture of excellence in data science and experimentation.
• Embody ourand