Senior AI Data Analyst — GTM AI & Analytics Team
Owns 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 Component
Contributes 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 Responsibilities
Executive & 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
Senior AI Data Analyst — GTM AI & Analytics Team
Owns 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 Component
Contributes 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 Responsibilities
Executive & 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 conduct background checks as part of our hiring process, in accordance with applicable laws and regulations in the countries where we operate. This may include verification of employment history, education, and, where legally permitted, criminal records. Any checks will be conducted lawfully prior to formal employment contracts being signed, with candidate consent, and information will be treated confidentially. Pigment is an equal opportunity employer. We believe diversity is a strength and fosters innovation. We are committed to enabling everyone to feel included and valued at the workplace. All qualified applicants will receive consideration for employment without regard to age, color, family, gender identity, marital status, national origin, physical or mental disability, sex (including pregnancy), sexual orientation, social origin, or any other characteristic protected by applicable laws. We may process your personal data in accordance with our HR Data Protection Notice.