Senior Business Analytics Specialist

Microsoft•,

2d•$106,400 - $222,600

About The Position

Turn complex business questions into trusted insights and scalable analytics. As a Senior Business Analytics Specialist, you will combine planning business intelligence (BI), rapid executive decision support, and semantic model ownership to strengthen commercial planning and performance. You will develop executive dashboards, investigate urgent business questions, and build governed data foundations for artificial intelligence (AI), self-service analytics, and Copilot-enabled experiences. You will work across business and technical teams to connect analytical rigor with practical recommendations, balancing immediate decisions with long-term improvements to data quality, architecture, and usability. We're looking for someone who combines business acumen with technical analytics expertise, thrives in ambiguity, and naturally leads with solutions and recommendations. The ideal candidate is hands on, curious, collaborative, and driven by a growth mindset with a passion for helping organizations make smarter, faster decisions through data.

Requirements

Master's Degree in Mathematics, Analytics, Engineering, Computer Science, Marketing, Business, Economics or related field AND 3+ years experience in data analysis and reporting, business intelligence, or business and financial analysis OR Bachelor's Degree in Statistics, Finance, 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 equivalent experience.
Translating complex, ambiguous business challenges into scalable analytics, reporting, and business intelligence solutions.
Hands-on experience with modern analytics platforms, including Microsoft Fabric, PowerBI, semantic models, and enterprise reporting solutions.
Knowledge of data architecture concepts, including data modeling, semantic layer design, data governance, and self-service analytics enablement.
Analytical problem-solving and judgment in ambiguous, time-sensitive situations, including exploratory analysis, diagnostics, and ad hoc investigations; ability to move quickly from a question to an evidence-based recommendation.

Nice To Haves

Master's Degree in Mathematics, Analytics, Engineering, Computer Science, Marketing, Business, Economics or related field AND 6+ years experience in data analysis and reporting, business intelligence, or business and financial analysis OR Bachelor's Degree in Statistics, Finance, Mathematics, Analytics, Engineering, Computer Science, Marketing, Business, Economics or related field AND 8+ years experience in data analysis and reporting, business intelligence, or business and financial analysis OR equivalent experience.

Responsibilities

Lead the design, development, and continuous improvement of planning BI, executive scorecards, dashboards, and performance reports.
Partner with stakeholders to define reporting requirements, key performance indicators (KPIs), business rules, and success measures.
Deliver scalable analytics for start-of-year business readiness, segmentation, quota planning, territory performance, coverage and resource planning, and investment allocation.
Drive adoption through accurate, accessible, and actionable insights.
Respond to executive requests and emerging strategic questions.
Frame ambiguous problems, select appropriate methods, and conduct root-cause analysis, diagnostics, trend and opportunity analysis, experimentation assessments, and scenario modeling while balancing speed with rigor.
Translate findings into concise executive narratives with clear implications and recommended actions.
Support leadership, planning, investment, and performance reviews; evaluate programs and operational decisions, identify growth drivers and risks, and measure outcomes using reusable analytical frameworks.
Own semantic models, analytical data products, and reporting architecture in Power BI and Microsoft Fabric.
Establish consistent enterprise metrics, business logic, data quality, governance, and lineage to support trusted, scalable self-service analytics.
Partner with engineering and analytics teams to consolidate models, simplify reporting, and reduce technical debt.
Optimize model performance, user experience, scalability, and platform efficiency through sound architecture practices.
Prepare and certify trusted, governed, discoverable data assets against enterprise standards.
Build AI-ready semantic foundations for natural language querying, Copilot, and agent-based analytics.
Partner with planning, finance, strategy, sales excellence, operations, engineering, and analytics teams to translate business questions into analytical requirements.
Act as a proactive advisor, using evidence and business judgment to influence decisions across technical and executive audiences.
Apply advanced analytical techniques across systems and processes, uphold reporting standards and quality assurance, and automate recurring analyses.
Explore new analytics, visualization, and AI capabilities, creating reusable assets that expand self-service and agent-powered insights.