Director, Revenue Strategy, Data & Analytics

NetBrain

20h•$180,000 - $205,000

About The Position

The Director, Revenue Strategy, Data & Analytics is the business's “brain trust” — equal parts strategist and data scientist. This role owns the annual operating plan (AOP), forecasting, and revenue science for the go-to-market organization, converting product telemetry and pipeline data into the annual plan, the quarterly forecast, and the weekly operating rhythm. The Director serves as the single source of revenue truth for Sales, Customer Success, and executive leadership, and is charged with intentionally applying AI to automate analytics, insights, and workflows that amplify seller and CSM productivity.

Requirements

8–10+ years in revenue operations, sales strategy, business intelligence, or related analytics roles, including 3+ years in a leadership capacity.
Proven ownership of an annual operating plan cycle — quota setting, capacity modeling, and territory design — at a B2B SaaS company.
Strong SQL and data modeling skills, with hands-on experience in BI/analytics tools (e.g., Tableau, Looker, Power BI) and Salesforce data models.
Experience building or partnering closely with data science teams on propensity-to-close, churn, and expansion models.
Track record translating pipeline and product telemetry into forecast and planning outputs used by executive leadership.
Executive-level communication skills; comfortable presenting forecast and plan outputs to CRO / executive staff.
Bachelor's degree in business, finance, economics, statistics, or a related field

Nice To Haves

MBA or advanced analytics degree a plus.
Experience piloting or scaling AI-enabled analytics and workflow tools within a go-to-market organization is a strong plus.

Responsibilities

Lead the annual operating plan process end to end, including quota setting, capacity modeling, and territory carve. Partner with Sales, Customer Success, and Finance leadership to align headcount, coverage, and targets to the company's growth plan.
Own and run the weekly “call of the number” cadence with sales and CS leadership. Synthesize Gong conversation signal into forecast inputs, and govern the commit / best-case / worst-case forecasting methodology used across the business.
Build and maintain propensity-to-close, churn, and expansion models fed by product usage and firmographic data. Partner with data engineering and BI to operationalize these models directly into seller and CSM workflows.
Own the strategy for the revenue data warehouse and drive identity resolution across product, marketing, CRM, and support systems, ensuring data governance and single-source-of-truth integrity.
Develop and maintain ideal-customer profiling scored on network complexity, device count, and change velocity. Refine total addressable market sizing and segmentation as go-to-market strategy evolves.
Intentionally identify, pilot, and scale AI tooling to automate analytics, insights, and workflows that amplify seller and CSM productivity across the revenue organization.