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Analyzes revenue, billings, forecasts, and pipeline data to identify risks and trends; builds predictive forecasting models; maintains Salesforce and SAP data integrity; develops dashboards; applies AI and machine learning to automate analysis; benchmarks market performance; and presents actionable insights to sales and executive leadership.
For over four decades, Cirrus Logic has been propelled by the top engineers in mixed-signal processing. Our rockstar team thrives on solving complex challenges with innovative end-user solutions for the world's top consumer brands. Cirrus Logic is also known for its award-winning culture, which was built on a foundation of inclusion and fairness, meaningful community engagement, and delivering enjoyable employee experiences at every turn. But we couldn’t do it without our extraordinary workforce – and that’s where you come in. Join our team and help us continue to make Cirrus Logic an exceptional place to grow your career!
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
- Bachelor's degree in Engineering, Business, Finance, Management Information Systems (MIS) or a related field.
- 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.
Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time.
Export control restrictions based upon applicable laws and regulations would prohibit candidates who are nationals of certain embargoed countries from working in this position without Cirrus Logic first obtaining an export license. Candidates for this role must be able to access technical data without a requirement for an export license. We are unable to sponsor or obtain export licenses for this role.
Cirrus Logic strives to select the best qualified applicant for any opening. Different approaches, ideas and points of view are both valued and respected. Employment decisions are made on the basis of job-related criteria without regard to race, color, religion, sex, national origin, age, protected veteran or disabled status, genetic information, or any other classification protected by applicable law.
Cirrus Logic Austin, Texas, USA Office
Cirrus Logic is nestled in the trendy West 6th neighborhood of Downtown Austin. Steps from our headquarters, you'll find incredible restaurants and nightlife, eclectic boutiques, independent book and record stores and the flagship Whole Foods Market and the Lady Bird Lake hike-and-bike trail.
Cirrus Logic Austin, Texas, USA Office
Cirrus Logic is nestled in the trendy West 6th neighborhood of Downtown Austin. Steps from our headquarters, you'll find incredible restaurants and nightlife, eclectic boutiques, independent book and record stores and the flagship Whole Foods Market and the Lady Bird Lake hike-and-bike trail.
Cirrus Logic Austin, Texas, USA Office
Cirrus Logic is nestled in the trendy West 6th neighborhood of Downtown Austin. Steps from our headquarters, you'll find incredible restaurants and nightlife, eclectic boutiques, independent book and record stores and the flagship Whole Foods Market and the Lady Bird Lake hike-and-bike trail.
Cirrus Logic Austin, Texas, USA Office
Just blocks away from ACL and hike and bike trails. Tons of restaurants and close to public transporation.
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center
