Data Scientist - Pricing

Overview The Cloud and AI Platforms Monetization organization is a big picture team that encourages a diverse and inclusive culture. We are growth strategists who enable the Microsoft mission by creating durable profit growth through high-impact monetization strategies, packaging, and pricing. We are seeking a Data Scientist - Pricing to drive yield optimization strategies for Azure infrastructure (e.g., virtual machines). In this role, you will translate revenue, hardware, and capacity data into actionable insights that maximize resource utilization, improve cost efficiency, and enhance customer experience. You will use your advanced analytics, machine learning, causal inference, and visualization skills to influence strategic decisions at scale 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. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities Data Analysis & Modeling: Analyze large-scale datasets to identify patterns, trends, and opportunities for improving yield and efficiency. Yield Optimization: Develop machine learning models to optimize resource allocation and pricing strategies. Cross-Functional Collaboration: Partner with business planning, 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. Build causal inference models (e.g., difference-in-difference, synthetic control) to measure the impact of business decisions. Data Visualization: Develop dashboards and other visuals to monitor key business trends, identify new opportunities, and translate findings to actionable insights. Thought Leadership: Stay current with industry trends in AI, cloud economics, and optimization techniques; share insights and best practices internally. Other: Embody our Culture and Values Qualifications 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. 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. Experience in Python, R, or similar languages Experience with Azure Machine Learning (ML) or equivalent cloud-based ML platforms. Experience working with large-scale data and distributed systems. Experience with yield or revenue management, pricing optimization, or cloud resource allocation. Data Science IC3 - The typical base pay range for this role across the U.S. is USD $102,100.00 - $202,200.00 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 $133,800.00 - $219,200.00 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.