Principal Applied Science Manager

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Do you have a keen interest in applying cutting-edge science to solve real-world problems at scale? Do you thrive in environments where you work with massive datasets and advanced machine learning techniques? Are you excited by the challenge of building intelligent systems that process trillions of records to deliver impactful experiences for millions of users?

At Microsoft AI, we are redefining what’s possible with data and AI. We’re seeking a Principal Applied Science Manager to help design and develop the next generation of big data and AI-driven capabilities.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

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.
• 1+ year(s) of people management experience.
  
• 3+ years of experience in statistics, machine learning, including deep learning, NLP, econometrics.

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.

Preferred Qualifications:

• 3+ years of people management experience.
• Experience moving applied research into shipped product features.
• Experience in structure un-scoped problems, define success metrics, and drive execution under uncertainty.
• Analytical mindset with a data-driven approach to problem-solving, consistently upholding high standards of scientific rigor.
• Proven track record of owning and delivering technically challenging projects with measurable impact.

Applied Sciences M5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft will accept applications for the role until November 17, 2025.

#MicrosoftAI #BING

• Drive strategic impact by identifying and leading high-leverage data science and analytics initiatives across multiple teams
• Drive model inference optimization and system integration to reduce cost, latency and system optimization
• Apply advanced statistical modeling, machine learning, and analytics techniques to tackle complex problems such as fraud/anomaly detection, opportunities and business impact analytics.
• Design E2E solutions and drive projects from concept to production in a fast-paced, dynamic environment.