Senior AI Data Analyst - Sales
Pigment · New York
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About the role
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
Skills
- Python
- SQL
- dbt
- Looker
- Tableau
- Snowflake
- AWS
- GCP
- Azure
- Spark
- pandas
- NumPy
- scikit-learn
- MLflow
- Kubernetes
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