Senior Data Scientist - Sales Insights

Our sellers are key to how customers and partners understand Microsoft’s products and strategies, but how do we align the conversations of thousands of sellers with each other and with the company’s strategy?  Making sure that the sellers are having the right conversations at the right time is key to the company’s success, and the Worldwide Incentive Compensation team connects strategy to seller behavior in one of the most important ways:  by determining how sellers get paid.

Worldwide Incentive Compensation (WWIC) is the team at Microsoft that is responsible for the design, implementation and operations related to the sales and incentive plans across all of Microsoft, impacting 40,000+ employees. Our vision is to embody best-in-class, design-to-deployment incentive compensation that inspires sellers to maximize their success and rewards and enables sustainable growth, share, and customer success.

We are searching for a Senior Data Scientist - Sales Insights to join our team. This role blends deep technical expertise in data science with business acumen in sales compensation. You will partner with cross-functional teams to design costing models, build machine learning solutions and AI agents, and deliver insights that influence compensation design and seller behavior. In addition, you’ll engage with diverse stakeholders, manage complex relationships, and drive innovation across the organization.

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. 

Required/Minimum Qualifications 

• 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 Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience
  • OR 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 equivalent experience.
• 5+ years of experience developing Big Data Pipelines and Dashboarding.
• 5+ years of experience developing in Python.
• 5+ years of experience with Machine Learning.

Additional or Preferred Qualifications

• 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 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 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 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

Microsoft will accept applications for the role until June 25, 2025.

Business Understanding & Impact 

• Demonstrate strong business acumen by aligning data science initiatives with strategic goals and proactively identifying opportunities for innovation and optimization.
• Leverage a deep understanding of incentive compensation design principles, levers, and mechanics to support the development and evaluation of compensation plans.
• Present plan analyses, rationale, and cost implications, ensuring alignment with Microsoft’s software, services, and sales Go-to-Market strategies.
• Collaborate with business teams to frame analytical questions, define hypotheses, and design experiments that inform product enhancements and client solutions.
• Engage with stakeholders to review the fairness, equity, and effectiveness of compensation design mechanics, using data-driven insights to guide improvements.
• Translate business context into analytical frameworks to solve complex compensation and performance challenges.  

 Data Science 

• Design, develop, and implement scalable methods, processes, and systems to consolidate and analyze large, diverse datasets—including unstructured “big data”—to generate actionable insights for business impact.
• Build and maintain data pipelines and automated processes to cleanse, integrate, and evaluate data from multiple sources, ensuring high data quality and availability.
• Apply advanced statistical techniques and machine learning models (e.g., classification, regression, NLP, forecasting) to solve complex business problems and drive measurable outcomes.
• Build AI agents that can deliver subject-relevant data and insights using natural language prompts, enabling intuitive access to analytics for business users.
• Leverage Microsoft’s AI/ML stack (Azure Machine Learning, Azure Databricks, Azure Cognitive Services) to deploy scalable models. 

Analytics & Evaluation

• Conduct scenario modeling and effective reviews of compensation plans.
• Evaluate model performance and ensure alignment with business objectives.
• Interpret and communicate insights clearly to technical and non-technical stakeholders, linking analytical findings to business objectives and recommending data-driven actions.

Stakeholder Engagement

• Act as a trusted advisor to sales and finance leaders, providing insights that influence compensation strategy and seller behavior.
• Collaborate cross-functionally with internal and external stakeholders to define project roadmaps, evaluate model performance, and ensure continuous improvement through feedback loops. 

Innovation & Continuous Improvement

• Contribute to the development of global tools and processes for compensation analytics.
• Identify opportunities for automation and process optimization.
• Stay current with industry trends and emerging technologies in data science and incentive design.

Governance and Compliance   

• Assesses programs for potential risks, verifying adherence to company policies and procedures when executing compensation practices.  
• Identifies control measures and governance needs.