Lead Analyst, Gtm Productivity Analytics

Wiz Wiz · Enterprise · United States · Remote · RevOps

Lead Analyst, GTM Productivity Analytics role focused on building and maintaining predictive capacity models, tracking GTM attainment and productivity, and conducting statistical analysis to drive sales performance. This role partners with GTM Leadership and FP&A teams, and requires experience in sales/financial modeling and modern data tooling.

What you'd actually do

  1. Serve as the primary analytical and systems owner for GTM productivity modelling and capacity planning, working closely with RevOps, FP&A, and GTM Leadership.
  2. Design, build, and maintain predictive capacity models based on productivity trends, historical data, and strategic hiring plans.
  3. Own and enhance the core models and dashboards that track GTM attainment, productivity, and performance against quotas.
  4. Conduct in-depth analysis to support the annual planning and quarterly forecasting processes to drive optimal sales behavior and performance.
  5. Drive alignment on standardized metrics and methodologies for productivity and attainment reporting across Operations, Finance, and Business stakeholders.

Skills

Required

  • 6+ years of progressive experience in analytics, data operations, consulting, or a similar data-focused role
  • strong emphasis on sales and/or financial modeling
  • Exceptional ability to synthesise data into actionable insights
  • communicate complex analytical findings and strategic recommendations to executive-level stakeholders
  • Experience designing, building, and maintaining scalable predictive models, data pipelines, and analytical tools
  • A strong understanding of how a high-growth GTM team operates
  • collaborative dynamics with FP&A teams

Nice to have

  • Experience with modern data tooling (e.g., BigQuery, dbt, Looker)

What the JD emphasized

  • primary analytical and systems owner
  • predictive capacity models
  • core models and dashboards
  • annual planning and quarterly forecasting
  • standardized metrics and methodologies
  • advanced statistical analysis
  • strong emphasis on sales and/or financial modeling
  • scalable predictive models, data pipelines, and analytical tools