OverviewThe
Global Marketing Engines and Experiences (E&E) team within Microsoft is responsible for delivering integrated marketing experiences for Microsoft by building, running, and innovating a globally scaled engine to deliver connected journeys that delight customers and create fans.
The
Media Data Science and Analytics team within E&E enables data-driven decision making by providing data products and insights to measure marketing's performance and impact, understand the customer experience, and develop systems of learning for marketers.
About YouAs a
Paid Media Data Analyst on the Media Data Science and Analytics team, you will play a critical role in establishing and promoting measurement frameworks that create better investment decision making. This will include developing solutions that are reusable, readily discoverable by decision makers, and self-service oriented, all while driving meaningful interpretation of data and supporting media optimization.
The optimal candidate thrives in fast-paced environments, demonstrates comfort with ambiguity, and collaborates effectively across teams and functional boundaries. Curiosity, a bias for action, and the ability to balance business context with technical expertise are essential.
In this role, you will support the rhythm of business by providing actionable recommendations to paid media stakeholders based on rigorous analysis and clear insights. You will leverage analytical techniques to develop scalable, efficient, and impactful data products while also diving deep into the details to uncover the story behind the data. You will bring sharp analytical thinking, strong communication skills, and the confidence to engage with executives and stakeholders across the business.
Key focus areas may include: campaign performance measurement, creative and audience testing, signal quality, perception measurement, survey design attribution and incrementality interpretation, funnel diagnostics, dashboard development, and translating learning agenda questions into repeatable analytical approaches.
ResponsibilitiesImprovement and Efficiency- Identify and promote methods that enhance efficiency in analytics and reporting.
- Ensure solutions are reusable, easily discoverable, and self-service oriented.
- Drive meaningful data interpretation to inform paid media business decisions.
- Recommend and socialize optimal methods for operationalizing, sharing, and scaling insights.
- Share knowledge and practical rationale for transitioning ad-hoc analyses to regular reporting features.
- Share domain knowledge to create clarity and ensure readiness to leverage data and insights effectively.
- Evaluate the viability of automated methods for data collection, reporting, and analysis.
Model Evaluation- Understand the relationship between analytical models or experiment designs and business objectives.
- Establish clear linkage between generated models or experiment designs and desired business outcomes.
- Assess the degree to which models meet business objectives and address gaps.
- Ensure alignment on definitions and standards across stakeholders.
- Define, design, and promote appropriate feedback and evaluation methods or experiment designs.
- Present results and findings to stakeholders.
Orchestration and Collaboration- Leverage working relationships within and across teams to ensure alignment and quality execution.
- Drive the adoption of recommended data sources and analysis practices.
- Proactively engage stakeholders to identify and act on opportunities to leverage data and resources.
- Consult across teams on decisions related to data sourcing, analyses, and interpretation of results.
Reporting and Sharing Results- Share insights and analytical experience through various means, including dashboards, reports, and visualizations.
- Synthesize and simplify details across analyses to highlight relevant findings.
- Identify opportunities to improve the efficiency of insights reporting techniques.
- Guide others and establish partnerships with stakeholders to ensure results are accessible and relevant.
Dashboard Builds- Develop and own Power BI dashboards to understand end-to-end campaign performance.
QualificationsRequired/minimum qualifications- 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.
Additional or preferred qualifications- 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 with perception measurement and survey design.
Data Analytics IC4 - The typical base pay range for this role across the U.S. is USD $106,400 - $203,600 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 $137,600 - $222,600 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
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
