Machine Learning Data Scientist

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The Worldwide Incentive Compensation (WWIC) team’s mission is to enable strategy, motivate sellers and reward results. In pursuit of this mission, the team designs and implements variable incentive-based compensation plans for more than 30,000 sellers, sales leaders and consultants across Microsoft. We are the experts in Incentive Compensation at Microsoft that are responsible for aligning incentive plans and targets (quotas) to motivate seller behavior and drive the company's strategies. We are also the end-to-end owners of incentive compensation processes and data which includes quota setting management, delivering timely and accurate pay-outs.

The Machine Learning Data Scientist will collaborate with key stakeholders across Business Operations & Sales Excellence, Finance, Mint Engineering, Finance Data & Experiences (FD&E), Plan Design, analytics and the broader WWIC organization. This role will lead the development of an AI agent to centrally manage budget restatements and proactively identify opportunities for quota adjustments based on both role-specific and overall business performance and forecasts.

The ideal candidate should be detail-oriented, able to translate business context and requirements into quota modeling. Excels with machine learning algorithms, statistical analysis, forecast modeling and capable of deploying models in Azure. Ability to digest complex problems, formulate creative solutions and successfully land those solutions with business partners. This individual should have attention to detail and ability to make practical decisions in times of ambiguity. The candidate must also have proven ability to work effectively in a large, cross-geography, cross-business virtual team environment. Success for this role requires the individual to be proficient in communication, both written and verbal, and must be able to support answering questions from business partners.

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 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.
• 3+ years of experience working with cloud tools and platforms such as Azure Synapse and Azure ML Studio, specializing in the development and deployment of AI models.
• 1+ year of experience working with Agentic AI & Language Learning Models including hands-on experience with LangChain or Auto-GPT.

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 until June 19, 2025.

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Business Understanding and Impact

• Demonstrate good business acumen, work with business partners to understand data and define and solve business problems and primary objectives

Data Preparation and Understanding

• Understand data pipelines, process flow and reports
• Acquires data necessary for successful completion of the project plan. Proactively detects changes and communicates to senior leaders.

Modeling and Statistical Analysis

• Leverage AI tools and data — such as quota baselines, territory assignment, and compensation plans — to help the field better understand quota-setting mechanics and build greater confidence in the process
• Leverage knowledge of machine learning solutions (e.g., classification, regression, clustering, forecasting, NLP, image recognition, etc.) and individual algorithms to identify the best approach to set quota.
• Effectively communicates with diverse audiences on data quality issues and initiatives.
• Develops a strong understanding of the Microsoft toolset in artificial intelligence (AI) and machine learning (ML) (e.g., Azure Machine Learning, Azure Cognitive Services, Azure Databricks).

Evaluation

• Understands relationship between selected models and business objectives. Ensures clear linkage between selected models and desired business objectives.
• Defines and designs feedback and evaluation methods.

Industry and Research Knowledge/Opportunity Identification

• Uses business knowledge and technical expertise to provide feedback to the engineering team to identify potential future business opportunities.

Business Management

• Collaborates with end customer and Microsoft internal cross-functional stakeholders to understand business needs. Formulates a roadmap of project activity that leads to measurable improvement in business performance metrics over time.

Customer/Partner Orientation

• Applies a customer-oriented focus by understanding customer needs and perspectives, validating customer perspectives, and focusing on broader customer organization/context. Promotes and ensures customer adoption by delivering model solutions and supporting relationships.
• Embody our culture and values