Senior Data Analyst

Microsoft’s Global Media and Partnerships team is a diverse, collaborative, solutions-oriented team committed to planning, activating and fiscally managing all paid media/advertising, strategic partnerships and agency relationships across Microsoft.  The team works across business groups to tie objectives, insights and innovation together to drive business impact through world-class media investment and measurement strategies. The Senior Data Analyst will play a critical role in identifying and promoting methods that create efficiency in core work related to analytics and reporting. 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 business decisions.

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.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Required/Minimum Qualifications

• 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 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 equivalent experience.
• 4+ years experience in marketing analytics specifically at a Fortune 100 or a media company.

Additional or Preferred Qualifications

• Bachelor's Degree in Statistics, 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 Master's Degree in 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.
• Demonstrated analytical and problem-solving skills.
• Proficiency in data analysis tools and software.
• Experience with statistical and machine learning models.
• Demonstrated understanding of data visualization techniques, BI systems
• Experience with Mobile app, Media, Social, influencer partnership

Data Analytics IC4 - The typical base pay range for this role across the U.S. is USD $103,800 - $200,300 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 $133,700 - $219,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Microsoft will accept applications for the role until January 14, 2025.   

Improvement 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 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 and business objectives.
• Establish clear linkage between generated models 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.
• Coach and mentor less experienced engineers as needed.
• Present results and findings to senior 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.

Other

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