Required/minimum qualifications
- Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field OR Master's Degree 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) or consulting experience
- OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR equivalent experience.
- Technical expertise as a developer, data scientist, or technical program manager.
- Proven experience and engagement within the AI category, building and launching generative AI solutions.
- Fluency in Python and at least one additional programming languages (example: SQL, C#, Java, R, JavaScript, Scala, Go, ReactJS etc).
- Experience leading internal change management and enablement efforts to support the adoption of new AI technologies.
Additional or preferred 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)
- OR Master'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)
- OR Bachelor'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.
- Solid foundational understanding of machine learning concepts and terminology (e.g., model training, fine-tuning, embeddings, evaluation metrics).
- Comfortable collaborating closely with engineering teams and making informed trade-offs based on technical constraints and business impact.
- Ability to think strategically and envision scalable platforms, while also diving deep into edge cases, architectural decisions, and implementation details.
- Highly self-directed and effective in decentralized, fast-paced environments.
- Deep empathy for internal users and a knack for translating complex business needs into elegant and usable product experiences.
- Demonstrated ownership across the full product lifecycle: requirements gathering, technical development, testing, launch, user training, and rollout.
- Proficient analytical skills and the ability to influence decisions with data and key performance metrics.
- Outstanding verbal skills, with the ability to align and influence a wide range of stakeholders.
- Familiarity with knowledge graph technologies and semantic data modeling.
- Deep familiarity with the Azure AI tech stack.
- Ability to operate at multiple altitudes—from strategic vision to tactical execution. This includes proficiency in communication skills, both written and presentation formats.
Data Science IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 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 $131,400 - $215,400 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 October 31, 2025.