Director, GTM Economics & Science
US$168,000 – US$269,000 / yr base salary
Posted 16 Jun 2026
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- On-Site
| Base salary | US$168,000 – US$269,000 / yr |
|---|
Field of studyApplied Economics, Econometrics, Economics, Quantitative Marketing (or related)
Study levelDoctorate
Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem.
This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us.
THE ROLE
Everpure is seeking a Director, GTM Economics & Science to drive go-to-market (GTM) efficiency by leading our causal measurement science vision. You will lead the development of advanced statistical methodologies to measure the incrementality of sales headcount, incentive investments, and customer-facing activities (e.g. workshops, proofs of concept, enablement collateral, events).
In this high-impact role, you will pioneer advanced statistical frameworks that separate true sales-driven lift from market noise, directly shaping global headcount planning and incentive designs. Collaborating closely with executive GTM Finance, Data Science, and Sales leadership, you will transform massive datasets into production-grade science deliverables that maximize global revenue and optimize ROI.
WHAT YOU'LL DO
- Own the Go-To-Market Causal Measurement Strategy: Architect and execute the long-term roadmap for measuring sales incrementality, partnering with senior Sales, Finance, and Operations executives to deliver highly accurate, actionable insights that guide global investment decisions.
- Design and Deploy Advanced Causal Models: Build, validate, and scale state-of-the-art observational models (such as causal forests, panel methods, and uplift models) in R or Python to isolate true headcount-driven lift and incentive plan performance from external market demand and noise.
- Drive Investment ROI and Strategic Allocation: Quantify the incremental impact of sales headcount, incentive modifications, and customer-facing programs (e.g., proofs of concept, workshops) for executive leaders (CFO, CRO, CMO) to directly influence headcount planning, NRR growth, and resource allocation.
- Operationalize Production-Grade Data Pipelines: Partner with Data Engineering, Analytics, and GTM Operations to establish robust, stable, and maintainable pipelines and data infrastructure, translating complex econometrics into automated dashboards and reusable frameworks for continuous business planning.
WHAT YOU BRING