Senior Data Scientist, Azure AI Yield Management
Microsoft
How you can make an impact
Microsoft Azure AI is at the forefront of enabling businesses to harness the power of artificial intelligence at scale. We are seeking a Senior Data Scientist, Azure AI Yield Management to drive yield optimization strategies across Azure AI services. This role will focus on leveraging advanced analytics, machine learning, and optimization techniques to maximize resource utilization, improve cost efficiency, and enhance the customer experience.
What our team offers
The Cloud and AI Platforms Monetization organization is a big picture team at our core that encourages a diverse and inclusive culture. We are respectful, collaborative, honest, accountable, and caring. Employees on the team can expect to have opportunities to grow their own experiences and career while shaping the future of the major businesses with data-informed strategies.
We are growth strategists who enable the Microsoft mission by creating durable profit growth through high-impact monetization strategies, packaging, and pricing. Our charter is significant and spans key growth engines for the company including Azure AI, developer, data, and Azure infrastructure, and our education and industry offerings and programs.
What I will do for you
- Champion your success with the team and with leadership
Provide opportunities to gain new experiences and build on your strengths
Support who you are as your authentic self
Make your career development a consistent priority
Responsibilities
Yield Optimization
- Develop and implement models to optimize resource allocation and pricing strategies for Azure AI workloads.
Data Analysis & Modeling
- Analyze large-scale datasets to identify patterns, trends, and opportunities for improving yield and efficiency.
Machine Learning Solutions
- Build predictive and prescriptive models using Azure AI and ML frameworks to forecast demand and optimize supply.
Cross-Functional Collaboration
- Partner with engineering, product management, and finance teams to align yield strategies with business objectives.
Experimentation & A/B Testing
- Design and execute experiments to validate optimization hypotheses and measure impact.
Scalability & Automation
- Develop scalable solutions and automation pipelines for continuous yield monitoring and improvement.
Thought Leadership
- Stay current with industry trends in AI, cloud economics, and optimization techniques; share insights and best practices internally.
Other
Qualifications
Required/minimum 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.
Additional or preferred qualifications
- Doctorate 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 Master'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 Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
Data Science 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
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. 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 with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.