Senior Data Analyst, Media Data Science & Analytics (eCommerce)

Role Overview

The Senior Data Analyst will serve as the analytical engine behind Microsoft’s eCommerce business, building and maintaining dashboards, reports, and self-serve analytics to give eCommerce partners timely visibility into commerce performance.

What You Will Do

The role involves building dashboards, analyzing funnel measurement, performing deep-dive analysis, and establishing trustworthy data foundations to drive business outcomes.

Why It Might Be a Fit

The ideal candidate will have experience querying and analyzing large datasets, integrating data from multiple sources, and communicating analytical insights to stakeholders.

Requirements

• Master’s Degree in Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field
• 2+ years experience in data analysis and reporting, data science, business intelligence, or business and financial analysis
• 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

Benefits

• Dental insurance
• Vision insurance
• Health insurance
• 401(k) or retirement plan
• Paid time off (vacation, sick leave, etc.)
• Flexible work arrangements (remote, flexible hours, etc.)
• Professional development opportunities
• Employee discounts
• Stock options or equity
• Bonus or commission
• Paid holidays

Tagged as: Data Analysis