Responsibilities

• Dashboards & Self-Serve Analytics - Build and maintain dashboards, reports, and self-serve analytics that give eCommerce, web, and marketing partners timely, accurate visibility into commerce performance across Microsoft's owned digital storefronts — so they can focus on acting on insights rather than wrangling data.
• Funnel Measurement - Analyze the web and eCommerce journey — from acquisition and on-site engagement through sign-up, checkout, conversion, and revenue — connecting customer behavior to the durable business outcomes our partners own, such as gross adds, conversion, and revenue.
• Deep-Dive Analysis - Investigate revenue, product and offer performance, customer behavior, and operational efficiency to surface actionable insights for partners, proactively bringing trends, anomalies, and opportunities forward without waiting to be asked.
• Trustworthy Data Foundation - Integrate data from multiple sources and partner closely with Data Engineering, Finance, Web data teams, and other partners to define metrics, validate data quality, and ensure analytical outputs are built on a reliable, well-modeled, analytics-ready single source of truth.
• Metric & Reporting Standards - Help establish consistent Key Performance Indicator (KPI) and metric definitions, reporting standards, and documentation practices that scale as the analytics function and its self-serve tools grow — so partner teams work from the same metrics language.
• Performance Driver Analysis - Identify and quantify drivers of performance change — including product and offer launches, merchandising and promotional changes, technical factors, seasonal patterns, and external events — so partners know what's real and what to act on.
• Experimentation - Support experimentation — such as A/B tests and web experience changes — to evaluate the impact of eCommerce improvements and give partners confidence in what to scale.
• Work Smarter with AI - Leverage AI-assisted and agentic tools such as Microsoft Copilot to accelerate analysis, automate recurring reporting workflows, and move from manual, reactive reporting toward proactive, scalable insight that reaches partners faster.
• Translate, Communicate & Partner - Turn ambiguous business questions into structured analytical frameworks, deliver clear findings to both technical and non-technical audiences through recurring readouts and deep-dive investigations, and collaborate cross-functionally with eCommerce, web experience, engineering, and marketing partners to prioritize improvements grounded in data.
• Other - Embody our Culture and Values

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.

Preferred

• Master’s Degree in Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 6+ 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 8+ years experience in data analysis and reporting, data science, business intelligence, or business and financial analysis OR equivalent experience.
• Experience querying and analyzing large datasets using SQL. Experience integrating data from multiple sources and validating data quality.
• Experience communicating analytical insights to stakeholders to inform decisions.
• Experience measuring web or eCommerce performance — such as acquisition, engagement, conversion, or revenue.
• Experience building dashboards or reusable reporting assets (e.g., Power BI).
• Experience enabling stakeholders through self-serve analytics and reporting. Experience using Python or similar tools for analysis or automation.
• Experience using Adobe Analytics or similar tools for measuring digital customer journeys.
• Familiarity with experimentation or attribution concepts.
• Experience using AI-assisted analytics tools (e.g., Microsoft Copilot) to accelerate analysis and automate reporting.
• Experience establishing KPI or metric definitions, reporting standards, or documentation for a growing analytics function.