Join Pigment: The AI Platform Redefining Business Planning
Pigment is the AI-powered business planning and performance management platform built for agility and scale. We connect people, data, and processes in one intuitive, feature-rich solution, empowering every team—from Finance to HR—to build, adapt, and align strategic plans in real time.
Founded in 2019, Pigment is one of the fastest-growing SaaS companies globally. Industry leaders like Unilever, Snowflake, Siemens, and DPD use Pigment daily to make more informed decisions and confidently navigate any scenario.
With a team of 600+ across Paris, London, New York, Toronto, San Francisco and Austin, we've raised nearly $400M from top-tier investors and were named a Visionary in the 2024 Gartner® Magic Quadrant™ for Financial Planning Software.
At Pigment, we take smart risks, celebrate bold ideas, and challenge the status quo—all while working as one team. If you're driven by innovation and ready to make an impact at scale, we’d love to hear from you.
Role Overview
We are seeking a Senior AI Data Analyst to join our GTM AI & Analytics Team. In this role, you will own the data strategy that powers our global Sales organization — helping us understand pipeline health, sharpen forecasting, drive our sales planning cycles (capacity, quota, territory, and headcount), and grow pipeline generation, conversion, and revenue across complex enterprise accounts and regions.
You'll operate at the intersection of analytics, data engineering, and business strategy, partnering with Sales leadership, RevOps, Marketing, and Finance to ensure decisions are grounded in trusted, scalable data.
This is an AI-forward role. We are already actively building the next generation of GTM analytics — where trusted definitions and version-controlled analytical "skills" let people ask questions to get answers on live data. You won't be experimenting with AI from scratch; you'll be extending a program that is already in production and helping scale it across the Sales org.
Leading with AI
AI is not a side project here, it's how our GTM AI & Analytics team already works. You will contribute to and scale GTM Cortex, our GTM analytics knowledge and orchestration layer:
- Author analytical "skills" as code — small, testable, version-controlled skills (atomic to composite) that run governed analyses on live data, maintained in our GitHub repo.
- Work in an AI-native workflow — author and iterate skills in Claude Code, querying live Pigment data safely through the Pigment MCP (our standard, governed way to query data with AI).
- Ground everything in a single source of truth — reference canonical metric and dimension definitions from our KPI Catalog rather than redefining logic ad hoc.
- Push adoption of AI-driven, self-service analytics across Sales — turning recurring questions ("why did win rate drop?", "where is pipeline coverage weakest?") into reusable skills instead of one-off analyses.
- Drive internal usage and adoption of our Analyst and Modeler AI agents within the Sales organization.
Key Responsibilities
Executive and Operational Analytics
- Own Sales executive dashboards: pipeline generation, pipeline coverage, forecast, win rates, sales cycle, quota attainment, ARR, and net-new vs. expansion
- Build advanced Pigment models and opportunity-level datasets for pipeline, capacity, and revenue analysis (including sales capacity and productivity modeling by region and segment)
- Standardize enterprise Sales metrics and definitions across teams and regions
Planning and Capacity Modeling
- Serve as the analytics backbone of our Sales planning cycles — annual and in-year — partnering closely with Sales leadership, RevOps, and Finance
- Build and maintain capacity, quota, and productivity models in Pigment
- Model headcount and territory scenarios, translating go-to-market strategy into bottoms-up pipeline and revenue targets
- Pressure-test planning assumptions against historical performance and run what-if scenarios to support key GTM decisions
Data Architecture and Automation
- Design and maintain scalable data pipelines from Salesforce, Pigment, Gong, Netsuite and other tools in our GTM stack
- Partner with Data Engineering on transformations (dbt, warehouse modeling)
- Build and scale AI skills on top of the Pigment MCP so analyses are reusable, governed, and automatable (recurring reports, event-driven alerts)
- Ensure data quality, governance, and documentation for all Sales data assets
Strategic Business Partnership
- Act as the analytics partner to Sales leadership and regional sales orgs
- Answer high-impact questions like:
- What is driving changes in win rate and sales cycle?
- Where is pipeline coverage weakest, and is capacity aligned to target?
- How does pipeline generation quality correlate to closed-won outcomes?
Enablement and Self-Service
- Build role-based reporting for Reps, Managers, and Executives
- Train Sales teams to use data in pipeline reviews, QBRs, forecast calls, and account planning
- Drive adoption of AI-driven, insight-first workflows across the Sales organization
Required Qualifications
- 5–8+ years in Data Analytics, Analytics Engineering, or Business Intelligence
- Advanced SQL and experience with enterprise-scale data warehouses (Snowflake, BigQuery, Redshift)
- Strong experience with SaaS and sales metrics at scale (ARR, pipeline generation, coverage, win rate, quota attainment, forecast accuracy)
- Hands-on experience with BI/planning tools (Pigment, Looker, Tableau, Power BI, Mode, etc.)
- Experience supporting enterprise Sales or RevOps teams, including GTM planning (capacity, quota, territory, or headcount modeling)
- Genuine enthusiasm for working in an AI-native analytics environment (LLM-assisted analysis, skills-as-code, governed data access)
Nice-to-Have
- Pigment experience
- Experience with Salesforce, Gong, Clari, Outreach/Salesloft, Segment, Amplitude, or similar
- Hands-on experience with AI coding/analysis tools (e.g. Claude Code) and/or MCP-based data access
- dbt, Python, or analytics engineering background
- Experience in B2B enterprise SaaS environments
- Familiarity with complex, multi-segment sales and forecasting motions
What Success Looks Like
- Sales leadership relies on your insights for pipeline, forecast, and capacity planning
- Pipeline and forecast risks are visible early and explained, not just reported
- Reps and managers use your dashboards and AI skills in every pipeline review and QBR
- A growing library of trusted, reusable Sales analytics skills reduces one-off requests
- Planning cycles run on your models — capacity, quota, territory, and headcount decisions are grounded in trusted scenarios
- Data is trusted, consistent, and embedded in Sales workflows
We are tageting an expected salary of $160k for this role
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.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
