Microsoft Member Technical Staff - Data Scientist 

United States, California, Mountain View 

690909893

to build systems that have true artificial intelligenceacross agents, applications, services, and infrastructure.

is responsible fordriving insights to build great products and

By applying to this Mountain View, CA position, youare required tobe local to San Francisco area and in office 3 days a week.

Required Qualifications:

• Doctorate 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)
  • ORMaster's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • ORBachelor's Degree 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 equivalent experience.
• 5+ years of experience inleveragingcomplex data, applied data science, developing sophisticated algorithms, executing large-scale A/B testing, andpossessingextensive product knowledge.
• Experience with creating metrics, predicting trend analysis, measuring traffic patterns, and assessing experimentation results.
• Proficiency in using one or more programming or scripting languages such as Python, R, or C# to work with data.

Preferred Qualifications:

• Previous experience in growth engineering or a growth-oriented role.
• Proven track record of driving key growth metrics, including acquisition, engagement, and retention, with concrete examples of initiatives built and shipped.
• Experience building data pipelines to support analytics and experiment scenarios.
• Experience working on product analytics to drive product improvements.
• Commitment to writing clean, maintainable, and well-documented code with a focus on application quality, performance, and security.
• Strong interpersonal skills and ability to work closely with cross-functional teams, including product managers, designers, and other engineers, while clearly communicating complex technical concepts to both technical and non-technical stakeholders.
• Enthusiasm for learning new technologies and staying up to date with industry trends, best practices, and emerging technologies in web development and AI.
• Ability to work in a fast-paced environment, manage multiple priorities, and adapt to changing requirements and deadlines.

Data Science IC4 - The typical base pay range for this role across the U.S. is USD $117,200 - $229,200 per year.

Data Science IC5 - The typical base pay range for this role across the U.S. is USD $137,600 - $267,000 per year.

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

offers for these roles on an ongoing basis.

• Drive product insights, opportunity analysis, and track metrics to support efforts across Microsoft Copilot.
• Drive new ways of instrumentation and measurement approach to evaluate new feature performance through experimentation
• Define metrics and build basic data pipelines to enable A|B experimentation for new features.
• Hands-on analysis of large volumes of telemetry data using various algorithms and tools including your own
• Articulate insights, storyboard with data and communicate to influence leadership and other key decision makers
• Find a path to get things done despite roadblocks to get your work into the hands of users quickly and iteratively.
• Enjoy working in a fast-paced, design-driven, product development cycle.
• Work collaboratively with our engineers, Product Managers, and marketing to take ambiguous projectsthat drive user growth, engagement, and retention. This includesidentifyingmarket opportunities,optimizingappflowsand improving product featuresandproposinginnovation solutions based on data.
• Embody ourand