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.