We're looking for a highly analytical, AI-fluent Sales Operations Analyst to own the end-to-end health of our revenue engine. This person will dig into billings, bookings, forecast, and pipeline/opportunity data to surface risks and trends before they hit the top line — and will use predictive modeling and AI tooling to make our forecasting sharper and more forward-looking than a traditional "look in the rearview mirror" operations function.
This is not a report-generation role. We need someone who can build models, question assumptions, and tell leadership what's about to happen — not just what already happened.
What You'll Do
- Analyze revenue, billings, forecast, and opportunity/pipeline data across the sales funnel to identify risks, anomalies, and emerging trends.
- Build and maintain predictive models for revenue forecasting (e.g., pipeline coverage models, win-rate/velocity forecasting, churn/renewal risk scoring).
- Benchmark company performance against market and industry trends; flag where we're outperforming or underperforming the market and why.
- Partner with Sales, Finance, and RevOps leadership to translate data findings into actionable recommendations.
- Own data integrity and reporting workflows across Salesforce (CRM/pipeline data) and SAP (billings/financial data).
- Design and maintain dashboards and forecasting models that reduce manual reporting and increase forecast accuracy.
- Apply AI/ML tools and techniques (e.g., LLMs, forecasting libraries, agentic workflows) to automate analysis, generate insights, and accelerate reporting cycles.
- Present findings to sales leadership and executives in a clear, decision-ready format.
Required Skills and Qualifications
- 3–5+ years in Sales Operations, Revenue Operations, FP&A, or a related analytics role.
- Hands-on experience with Salesforce (reporting, dashboards, pipeline/opportunity data structures).
- Hands-on experience with SAP (billings, revenue, financial reporting modules).
- Demonstrated experience building predictive/statistical models for forecasting (regression, time-series, or ML-based forecasting).
- Strong SQL skills and experience with a BI tool (Spotfire, Power BI, Looker, or similar).
- Practical, hands-on fluency with AI tools — using LLMs/AI copilots (e.g., Claude, ChatGPT, Copilot) to accelerate analysis, and/or building AI-assisted workflows, not just "aware of AI".
- Strong business acumen — able to connect data patterns to real commercial risk (churn, slipping deals, forecast gaps, market softening).
- Excellent communication skills; able to present technical findings to non-technical executive audiences.
Preferred Skills and Qualifications
- Experience with Python or R for statistical modeling and forecasting (pandas, scikit-learn, statsmodels, Prophet, etc.).
- Experience with Salesforce CRM Analytics / Einstein Forecasting, or SAP Analytics Cloud.
- Experience building or working with AI agents/automations (e.g., using APIs, RPA, or agentic frameworks) to streamline recurring analysis.
- Background in SaaS, subscription, or usage-based revenue models.
- Experience with market/competitive intelligence tools (e.g., analyst reports, industry benchmarking data, PitchBook, Gartner).
- Familiarity with data visualization/storytelling best practices for executive reporting.
- Prior experience supporting a forecast call or QBR process directly with sales leadership.
Nice to Have
- Certifications: Salesforce Certified Administrator or Advanced Analytics, SAP Analytics certification.
- Experience with prompt engineering or building custom GPTs/AI assistants for internal reporting workflows.
- Exposure to CPQ, billing automation, or deal desk processes.