Sr Data Analyst - Quota Delivery

Microsoft•Seattle, WA

About The Position

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 aligning company aspirations with seller incentives. 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 40K+ 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. The Sr. Data Analyst - Quota Delivery is key in enabling the benefits of AI agents in Quota Setting process. It blends technical expertise in data analytics with business acumen in sales compensation. You will partner with cross-functional teams to deliver quotas to sellers, build, and deploy AI agents, and deliver insights that influence processes and seller behavior. In addition, you will engage with diverse stakeholders, manage complex relationships, and drive innovation across the organization.

Requirements

Master's Degree in Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 2+ years experience in data analysis and reporting, data science, business intelligence, or business and financial analysis OR Bachelor's Degree in Statistics, Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 4+ years experience in data analysis and reporting, data science, business intelligence, or business and financial analysis OR equivalent experience.
Citizenship & Citizenship Verification: This position requires verification of U.S citizenship due to citizenship-based legal restrictions. Specifically, this position supports United States federal, state, and/or local United States government agency customers and is subject to certain citizenship-based restrictions where required or permitted by applicable law. To meet this legal requirement, citizenship will be verified via a valid passport.

Nice To Haves

Experience with Artificial Intelligence (AI) Ethics issues around fairness, transparency, accountability, and ethics in relation to the use of artificial intelligence (AI).
Experience detecting and correct corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate, or irrelevant parts of the data and then replacing, modifying, or deleting as needed to maintain the integrity of the data.
Experience with technical and business processes used to combine data from disparate sources into meaningful and valuable information to deliver a complete data integration solution.
Experience maintaining and assuring the accuracy and consistency of data over its entire lifecycle in design, implementation, and usage of systems. This includes knowledge of data governance practices to ensure data quality and defined risk management surrounding the handling of data.
Experience examing large databases to discover patterns and generate new information. This includes the use of machine learning, statistics, and database systems and aims toward extracting information from a data set and transforming the information into a comprehensive structure for further use.
Experience with data modeling procedures and the ability to identify and clearly define the business data entities (for example, persons, places, things, concepts, events), attributes, and relationships between them. This includes the ability to read, understand, and develop test data models.

Responsibilities

Applies deep knowledge of the business, data landscape, tools, technologies, and data lineage across multiple domains.
Connects business topics to relevant data sources and external trends, anticipating data and business requirements.
Proactively frames business questions into analytical solutions and identifies opportunities to enhance or automate data infrastructure and insights.
Builds strong cross‑functional connections to enable effective data sourcing, integration, and evaluation of business questions.
Stays current on analytics tools, best practices, and regulatory changes, while coaching others to broaden business and data understanding.
Lead continuous improvement and innovation across quota delivery processes to enable speed, quality, and strategic alignment. Initially focus on Microsoft Federal Organization and then expand to other business groups.
Own end-to-end product lifecycle including requirement gathering, prioritization, roadmap creation, delivery execution, and post-launch measurement.
Drive quality and scale across quota management processes and tools, including future-year business rules, in-year governance, standardized workflows, and tool functionality.
Apply large language models (LLMs), prompt engineering, evaluations, and agentic workflows to quota delivery and governance challenges.
Assess existing quota and WWIC systems, data flows, and processes to identify AI-led automation and productivity opportunities.
Build and iterate rapid prototypes of AI-enabled solutions improving decision support, data quality, and user experience.
Drive continuous learning and AI capability building across the Quota Delivery team
Establish feedback loops to measure AI impact on productivity, quality, and operational efficiency.
Understands relationship between analytical model(s) and business objectives. Ability to create a clear connection between generated data models and business goals to evaluate how well these models achieve those objectives, while also identifying any gaps or missed areas.
Ensures alignment on definitions and standards across stakeholders and defines, designs, and promotes the use of appropriate feedback and evaluation methods. Coaches and mentors are less experienced analysts than needed. Presents results and findings to senior stakeholders.
Own delivery of data-backed insights on quota strategy execution, effectiveness, risks, and opportunities.
Leverage seller performance and quota data to inform current-year execution and future-year quota strategy and governance.
Act as a trusted advisor to senior stakeholders, translating complex data and AI-driven insights into clear business narratives.