Data Analyst

NetBrain

6d•$130,000 - $155,000

About The Position

NetBrain is seeking a Senior Data Analyst to join its Revenue Strategy, Data & Analytics team. This team is responsible for planning, forecasting, and providing revenue insights across the go-to-market organization. The Senior Data Analyst will convert product telemetry and pipeline data into key financial and operational metrics, serving as the central source of revenue truth.

Requirements

6-8 years of experience in revenue analytics, sales/marketing data science, or a similar function at a B2B software or SaaS company.
Demonstrated ownership of an annual operating plan or quota-setting process, with hands-on experience in capacity modeling and territory design.
Expert-level SQL (window functions, CTEs, query optimization) and data warehouse experience (Snowflake, BigQuery, or Redshift).
Deep Salesforce CRM proficiency (SOQL, object relationships, custom reporting, data quality management).
Hands-on forecasting experience using commit/best/worst methodology.
Experience building predictive models (propensity-to-close, churn, expansion) using Python or R.
Strong working knowledge of GTM segmentation (ICP scoring, TAM sizing, firmographic/technographic modeling).
Proven ability to translate complex analytical findings into clear executive-facing narratives and recommendations.

Nice To Haves

Experience integrating product usage/telemetry data into revenue models.
Familiarity with identity resolution across disparate GTM data sources (marketing automation, CRM, product, support).
Prior work applying AI/ML to GTM workflows (automated insight generation, NLP on call transcripts, or workflow automation).
Familiarity with AI-assisted signal tools such as Gong.

Responsibilities

Own the annual operating plan (AOP) process, including quota setting, capacity modeling, territory carve, and segment-level planning.
Run the weekly forecast using commit/best/worst methodology, synthesizing deal signals, pipeline movement, and coverage ratios.
Build and maintain propensity-to-close, churn, and expansion models using product usage telemetry and firmographic data.
Architect and maintain the revenue data warehouse, ensuring identity resolution across product, marketing, CRM, and support data sources.
Develop and refine ideal-customer profiles based on network complexity, device count, and change velocity; own TAM sizing and segment definitions.
Leverage AI to automate analytics, surface insights, and streamline GTM workflows.
Partner with Sales, Marketing, Finance, and Customer Success leadership to build self-service reporting and drive data-driven decision-making.
Define, document, and maintain key revenue metrics and their calculation logic.