Senior AI Data Analyst - GTM AI & Analytics TeamOwns the data strategy powering the global Sales org - pipeline health, forecasting, sales planning (capacity, quota, territory, headcount), and pipeline/revenue growth across enterprise accounts. Sits between analytics, data engineering, and business strategy; partners with Sales leadership, RevOps, Marketing, and Finance.
AI-Native ComponentContributes to GTM Cortex, the company's GTM analytics/orchestration layer:
- Builds analytical "skills" as version-controlled code (atomic to composite), tested and maintained in GitHub
- Works in Claude Code, querying live Pigment data through the Pigment MCP
- References a central KPI Catalog rather than redefining metrics ad hoc
- Converts recurring sales questions into reusable skills instead of one-off analyses
- Drives adoption of Analyst/Modeler AI agents across Sales
Key ResponsibilitiesExecutive & Operational Analytics
- Owns dashboards: pipeline generation, coverage, forecast, win rates, sales cycle, quota attainment, ARR, net-new vs. expansion
- Builds Pigment models and opportunity-level datasets for pipeline, capacity, revenue
- Standardizes metrics/definitions across teams and regions
Planning & Capacity Modeling
- Analytics backbone for annual and in-year sales planning cycles
- Builds/maintains capacity, quota, productivity models in Pigment
- Models headcount and territory scenarios; runs what-if analysis against historical performance
Data Architecture & Automation
- Designs data pipelines from Salesforce, Pigment, Gong, Netsuite, etc.
- Partners with Data Engineering on dbt/warehouse transformations
- Builds AI skills on Pigment MCP for recurring reports and event-driven alerts
- Owns data quality, governance, documentation
Business Partnership
- Analytics partner to Sales leadership and regional orgs
- Answers questions like: what's driving win rate/cycle changes, where is coverage weakest, how does pipeline quality
Enablement- Builds role-based reporting for reps, managers, execs
- Trains Sales teams on data use in pipeline reviews, QBRs, forecast calls
- Drives adoption of AI-driven workflows
Required Qualifications- 5-8+ years in Data Analytics, Analytics Engineering, or BI
- Advanced SQL; experience with Snowflake/BigQuery/Redshift
- Strong SaaS/sales metrics background (ARR, pipeline gen, coverage, win rate, quota attainment, forecast accuracy)
- Hands-on BI/planning tools (Pigment, Looker, Tableau, Power BI, Mode)
- Experience supporting enterprise Sales/RevOps, including GTM planning
- Genuine interest in AI-native analytics (LLM-assisted analysis, skills-as-code, governed data access)
Nice to Have- Pigment experience
- Salesforce, Gong, Clari, Outreach/Salesloft, Segment, or Amplitude
- Claude Code or MCP-based data access experience
- dbt, Python, or analytics engineering background
- B2B enterprise SaaS experience
- Familiarity with complex, multi-segment sales/forecasting motions
Success Metrics- Sales leadership relies on insights for pipeline, forecast, capacity planning
- Risks surfaced early, not just reported
- Dashboards/AI skills used in every pipeline review and QBR
- Growing library of reusable analytics skills reduces one-off requests
- Planning cycles run on these models
- Data is trusted, consistent, embedded in workflows
We are targeting a total comp package of $160kOTE for this role
