Sales Operations Analyst, AI & Revenue Intelligence

Cirrus Logic•Austin, TX

About The Position

Cirrus Logic is seeking a highly analytical, AI-fluent Sales Operations Analyst to own the end-to-end health of their revenue engine. This role involves analyzing billings, bookings, forecast, and pipeline/opportunity data to identify risks and trends. The analyst will utilize predictive modeling and AI tooling to enhance forecasting accuracy and provide forward-looking insights. This is not a report-generation role; the focus is on building models, questioning assumptions, and informing leadership about future outcomes.

Requirements

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.
Applicants must be authorized to work for ANY employer in the U.S.
Candidates for this role must be able to access technical data without a requirement for an export license.

Nice To Haves

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.
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.

Responsibilities

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.