Commercial Analytics Leader

Megaport•Washington, WA

About The Position

The Commercial Analytics Leader is the primary strategic interface between commercial leadership and the organization’s data, analytics, and data-science capabilities. The role connects trusted data, technical analytics, and business strategy to make accurate commercial intelligence continuously available, understandable, and actionable across core and expansion sales motions. It focuses on improving sales performance, revenue reporting, and commission-attainment metrics, with a planned progression into predictive analytics, commercial optimization, AI-powered intelligence, and governed self-service capabilities. The Leader will build an on-demand commercial intelligence engine that moves the business beyond static reports and dashboards, connecting data and insights to recommendations, better decisions, and measurable business outcomes. The role calls for a builder’s mindset and combines commercial leadership, analytical rigor, technical fluency, and the ability to influence decisions across organizational boundaries. The position owns the commercial analytics strategy, roadmap, and operating standards; the governance and architecture of RevOps performance reporting; and the development of trusted, reusable analytical assets. It partners across commercial teams and technical functions to improve data reliability, translate analysis into executive recommendations, support revenue optimization, enable responsible AI-powered analytics, and develop governed self-service capabilities.

Requirements

At least 5 years of progressive experience in commercial analytics, revenue analytics, business intelligence, statistical analyses, or a closely related analytical discipline, including substantial ownership of business-facing analytics.
Demonstrated success translating complex commercial data into executive-level recommendations and measurable business improvements.
Experience designing governed metrics, scalable reporting architectures, or equivalent frameworks supporting consistent reporting across multiple systems and stakeholder groups.
Strong understanding of B2B revenue operations, CRM data, pipeline and forecast management, sales compensation and commission attainment, customer lifecycle metrics, and expansion revenue.
Practical proficiency with SQL and Power BI or comparable enterprise tools.
Experience partnering with Data Engineering and Data Science to validate data pipelines, analytical models, business rules, and model outputs.
Demonstrated ability to establish data governance, metric definitions, reconciliation standards, reporting controls, and trusted self-service analytics.
Strong executive communication, stakeholder management, structured problem-solving, and change leadership skills.

Nice To Haves

Familiarity with Python or R, statistical analysis, data modeling, pacing, and predictive modeling or forecasting.

Responsibilities

Define and own the commercial analytics strategy, roadmap, and operating standards across brands, products, regions, and commercial motions.
Translate executive priorities and commercial objectives into a prioritized portfolio of analytical capabilities, business questions, and measurable outcomes.
Progress commercial intelligence from descriptive performance reporting to diagnostic, predictive, and prescriptive AI-enabled decision intelligence.
Own the commercial architecture and governance of RevOps performance reporting, including metric definitions, calculation rules, analytical views, reporting standards, and management cadences.
Build a coherent reporting framework based in Salesforce, collaborating with Power BI, billing sources and finance systems, marketing systems, and other relevant commercial data tools.
Reduce duplicated calculations, conflicting reports, spreadsheet dependencies, and legacy dashboards through standardized, reusable analytical assets.
Partner with RevTech, Data Engineering, Data Science, Finance, and source-system owners to validate analytical logic, reconcile discrepancies, identify data gaps, and resolve recurring quality issues.
Establish standards for data freshness, reconciliation, completeness, lineage, calculation validation, change management, and issue escalation.
Make analytical reliability, traceability, and business confidence measurable operating priorities.
Translate complex data and analytical outputs into concise narratives connecting performance, drivers, implications, recommendations, actions, and outcomes.
Serve as an analytical partner to Sales and GTM Leadership, RevOps, Customer Success, Marketing, Finance, Product, and Strategy; support business reviews, forecasting, strategic planning, and other commercial decisions.
Analyze performance across new-logo acquisition, pipeline conversion, account expansion, cross-sell, renewals, channel partnerships, and other relevant revenue motions.
Identify drivers of attainment, forecast variance, sales productivity, deal velocity, customer growth, and revenue leakage; evaluate trends to uncover growth opportunities and execution constraints.
Partner with RevTech and Data Science to make governed commercial metrics and contextual business definitions accessible to approved AI tools, analytical agents, and natural-language interfaces.
Ensure AI-generated conclusions are grounded in approved data and metric definitions, with safeguards against unsupported conclusions and unauthorized data access.
Develop governed self-service analytical capabilities that help business users answer common questions independently without creating competing versions of the truth.
Design analytical experiences around user decisions and embed insights into existing commercial workflows where practical.
Establish standards for metric interpretation, analytical literacy, documentation, access, training, and responsible use.
Identify upstream process, integration, data-model, and instrumentation improvements needed to strengthen the analytical foundation.
Coordinate delivery across commercial stakeholders, RevTech, Data Engineering, Data Science, Finance, and Technology without duplicating their functional responsibilities.
Continuously improve the speed, consistency, reliability, accessibility, and business impact of commercial intelligence.