Senior Data Analyst

Microsoft•Redmond, WA

3d•$106,400 - $222,600

About The Position

The Senior Data Analyst will join Microsoft’s GCS Business Strategy and Resource Planning team within the Customer & Commercial Success organization. The role connects business strategy, financials, planning assumptions, and complex data to develop forward-looking resource plans and business recommendations. The analyst will address complex cross-organizational problems, manage competing priorities, and engage with stakeholders and senior leaders in a matrix organization. The position focuses on resource allocation, demand forecasting, and capacity allocation models tailored to business needs. It requires translating complex quantitative and qualitative data into actionable insights that support delivery strategy, resource recommendations, and business decisions. The analyst will work across finance, Customer Success leadership, offerings design teams, and regional planning teams, and provide analytics and insights to senior leadership.

Requirements

Master’s degree in Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics, or a related field and 2+ years of experience in data analysis and reporting, data science, business intelligence, or business and financial analysis; or bachelor’s degree in a listed or related field and 4+ years of such experience; or equivalent experience.
Able to influence others through logical and strategic thinking and motivate a diverse organization toward a collective goal.
Sound judgment incorporating analysis, a pragmatic approach, business goals, and stakeholder priorities.
Able to synthesize disparate information quickly into clear recommendations, actions, and decisions.
Strong project management skills and ability to drive results across distributed stakeholders and multiple projects.
Detail-oriented, strategic, and data-driven, with the ability to work with quantitative and qualitative data.
Able to work independently in a dynamic environment, manage ambiguity and competing priorities, and produce strong results.
Comfortable moving between strategy and execution details and managing multiple projects.

Nice To Haves

Master’s degree in Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics, or a related field and 6+ years of experience in data analysis and reporting, data science, business intelligence, or business and financial analysis; or bachelor’s degree in a listed or related field and 8+ years of such experience; or equivalent experience.
Knowledge of Microsoft’s Customer Success business.
Experience in planning, analytics, finance, and operations.

Responsibilities

Design and implement resource allocation and demand forecasting models with business planners, delivery and resourcing strategy leads, and finance.
Design and implement capacity allocation models by role, customer segment, workload, and other required dimensions; align models with business strategy and validate them with Customer Success stakeholders.
Continuously evaluate and evolve models, methodologies, and assumptions to improve accuracy, address changing business requirements, and support sound decisions.
Translate complex data into clear, actionable narratives and provide data-driven insights and recommendations on delivery strategy and resource recommendations.
Collaborate with finance, Customer Success leadership, and offerings design teams to incorporate business changes into demand forecasts and capacity allocation models.
Analyze complex quantitative and qualitative datasets, identify trends and risks, challenge assumptions, and convert findings into concise, actionable recommendations.
Support resolution of complex business problems that affect resource allocation.
Identify trends in business, financial results, and delivery data to improve model requirements and insights.
Partner with regional planning teams to implement the capacity model and provide insights and clarity about modeling assumptions and data points.
Provide senior leadership with analytics and insights during regular review sessions.
Drive complex cross-functional issues to resolution under tight timelines while managing shifting priorities and making progress despite ambiguity or incomplete information.