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Large Language Models (LLMs) are fundamentally transforming how we build solutions for our customers. The People Analytics team is focused on developing robust, scalable, and LLM-powered solutions that enable customers to access and understand their data more efficiently. Our work spans multiple domains—data science, engineering, and AI—bringing them together to deliver impactful insights and user experiences.

As an **Principal Applied Scientist** on the People Analytics team, you will leverage your expertise to drive innovation and lead efforts to design, develop, and deliver scalable, high-quality solutions powered by LLMs. This role offers a unique opportunity to work on end-to-end systems that integrate data, engineering, LLMs, and user experience. The position is based in Redmond, WA, USA, and requires working from the office at least three days per week.

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.

Responsibilities

+ Serve as a team expert on changes in industry trends, products, and other advances, and apply this knowledge to influence product needs.

+ Review business and product requirements, incorporate engineers and product manager, and provide strategic direction for problem solving.

+ Ensure scientific rigor, support the development of methods, and apply your expertise to support business impact.

+ Document work and experimentation results and share findings to promote innovation.

+ Provide guidance when capturing processes and contribute to ethics and privacy policies related to research processes and data collection.

+ Design end-to-end solutions and lead the team in integrating AI capabilities into the product.

+ Embody our culture and values .

Qualifications

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.

+ Solid engineering background with hands-on experience integrating AI projects into customer solutions.

+ Experience building or evaluating LLM-based or generative AI solutions in production environments

+ Ability to translate ambiguous business problems into measurable ML problems and deliver scalable solutions.

+ Deep understanding of experiment design, model evaluation, and responsible AI principles (fairness, interpretability, bias mitigation).

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:

+ Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research)

+ OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)

+ OR equivalent experience.

+ 5+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).

+ 2+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker.

+ 5+ years experience conducting research as part of a research program (in academic or industry settings).

+ 3+ years experience developing and deploying live production systems, as part of a product team.

+ 3+ years experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.

+ Effective communication skills—able to explain complex models or research outcomes to technical and non-technical stakeholders.

Applied Sciences IC5 - 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 October 24, 2025.

Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations (https://careers.microsoft.com/v2/global/en/accessibility.html) .