Senior Applied Scientist
Microsoft
Senior Applied Scientist
Redmond, Washington, United States
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Overview
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.
Qualifications
Required Qualifications:
- Bachelor'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 Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
- 1+ year(s) experience in data science, machine learning, experimentation, and AI, with a strong track record of delivering impactful results.
- 1+ year(s) experience of LLM in finetuning, evaluation techniques and industry best practices.
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 6+ 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.
- 3+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
- 3+ years experience conducting research as part of a research program (in academic or industry settings).
- 1+ year(s) experience developing and deploying live production systems, as part of a product team.
Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $158,400 - $258,000 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 September 15th, 2025.
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Responsibilities
- You will master and gain expertise in broad areas of AI and ML, including trending research techniques. You’ll also gain deep knowledge of building enterprise intelligence on office user’s data.
- You will review business requirements and incorporate research to meet business goals. You ‘ll provide strategic direction for the kinds of data used to solve problems and apply deep subject matter knowledge to support business impact.
- You will participate in onboarding of team members and assist in developing academics to be members of multidiscipline teams. You’ll identify new research talent to join Microsoft and collaborate with the academic community to develop the recruiting pipeline.
- You will document work in progress and experimentation results and share findings to promote innovation. You’ll also use your deep understanding of fairness and bias to contribute to ethics and privacy policies related to research processes and data collection.
- You will collaborate with a multidisciplinary team to create scalable and ethical AI solutions.
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