The Microsoft Advertising Data Science & Analytics team combines deep data analysis and strategic thought partnership to create modern, Artificial Intelligence (AI) enabled insights and solutions. We are a Global Center of Excellence for cross-functional partners (i.e. Customer Success, Sales, Product, and more) that support Microsoft Advertising technology platform clients, empowering them to make qualityrevenue-driving decisions across Managed and Programmaticad channels. We analyze data, build tools, automate insights, andprovide white-glove consultation to influence strategic, technical,and tactical decisions. As a Senior Business Analyst you will be supporting the success of our most strategic client engagements, in partnership with other client-facing teams in Customer Success and Sales. If you have a passion to work cross-functionally, make clients successful, solve monumental challenges and work to improve systems, then this is the role for you!
Qualifications:
Required Qualifications:
- Bachelor’s Degree in Statistics, Mathematics, Analytics, Engineering, Computer Science, Marketing, Business, Economics or related field AND 4+ years experience in data analysis and reporting, business intelligence, or business and financial analysis
- OR Master’s Degree in Mathematics, Analytics, Engineering, Computer Science, Marketing, Business, Economics or related field AND 2+ years experience in data analysis and reporting, business intelligence, or business and financial analysis
- OR equivalent experience.
Preferred Qualifications:
- 5+ years experience in data analysis and reporting, business intelligence, or business and financial analysis.
- Experience with Yield Analytics (Previously known as Yieldex, a Microsoft forecasting product)
- Experience in Yield and Monetization for publishers
- Experience with the legacy AppNexus/Xandr tech platform
- Experience working in strategic client partnerships
Business Analytics IC4 – The typical base pay range for this role across the U.S. is USD $101,200 – $194,800 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 $130,000 – $213,200 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 .
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form .
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
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Responsibilities:
- Build understanding of the business across multiple areas, link internal business topics to relevant external trends, and anticipate business problems. Proactively anticipate business questions and identify appropriate insights or plausible analytical solutions to suggest in response. May coach others to help them broaden business knowledge.
- Leverage appropriate types and sources of data and/or metrics, understand how business needs translate into data requirements and evaluate sufficiency of data sources, determine needs for integrating additional data, and identify, anticipate, and address gaps and data quality issues, in partnership with other teams. Leverage relevant data, frameworks, and/or analyses from other teams, and ensure that data access and quality issues are addressed.
- Apply expertise to determine ideal analytical tools and techniques to address business questions. Guide and partner with others to execute analyses, resolve analytical challenges, interpret results across relevant contexts, and provide actionable insights and recommendations to business stakeholders and clients. Critically evaluate assumptions about data or analysis methods to ensure they are appropriate for answering business questions in context and provide feedback on features and functions of analytical tools (e.g., algorithms, statistical models) developed by Engineering or Data Scientists.
- Develop appropriate presentations that tell stories of analyses, including dashboards, reports, data visualizations, self-service platforms, slides, and talking points that highlight relevant insights. Synthesize details across analyses and reporting platforms into a cohesive story that serves to inform business decisions, and identifies opportunities to improve efficiency of reporting and presentations. Guide others to ensure presented results are accessible, and provide information accurately, clearly, and with sufficient relevance to influence decision making for intended audience(s).
- Determine factors and/or data types to include in the evaluation of the impact of business, product, and/or operational decisions that provide relevant assessments of impact. Ensure that evaluations can account for anticipated risks and applies learnings from previous evaluations. Synthesize results across evaluation instances, identifies relevant connections to other work, and makes recommendations for next steps linked to strategic business goals.
- Leverage working relationships within and across teams to ensure quality data sources, methodologies, as well as the appropriate application of analytical tools and processes, and drive their adoption, to facilitate relevant insight generation, reporting, and interpretation. Proactively engage stakeholders to identify and act on opportunities to leverage resources and solutions that were instrumental to success in similar contexts, and consult across teams on decisions related to analyses, insights reporting, and/or their interpretation
- Identify and promote methods that create efficiency in core work related to analytics and reporting that are reusable, readily discoverable by decision-makers, self-service, and directed to meaningful interpretation of data that drive business decisions and impact. Recommend and socialize optimal methods for sharing, standardizing, and scaling insights. Evaluate the viability and relevance of automated methods for use in reporting, and/or analysis to recommend when they should become standard practices.