Sr Analyst, Customer Intelligence

Summary

Avalara is building an AI-first operating model to predict customer needs and improve revenue retention. The Sr Analyst, Customer Intelligence will own the analytical foundation behind CX360, defining scoring frameworks and predictive indicators to convert customer signals into actionable insights.

Responsibilities

• Ensure CX360 delivers accurate, trusted, decision-ready customer intelligence across Product, CX, Operations, and executive leadership, with clear ownership of scoring integrity
• Define and govern scoring frameworks, lifecycle metrics, friction models, and prioritization thresholds to ensure consistency, transparency, and business relevance
• Collaborate with Data Science, Architecture, Engineering, and Product to validate data integrity and strengthen insights through predictive modeling and sentiment analysis
• Build and evolve customer intelligence analytics including segmentation, cohort analysis, and driver attribution tied directly to retention and efficiency outcomes
• Quantify the financial and operational impact of customer friction using revenue and cost modeling to establish measurable prioritization standards
• Translate complex analytics into structured, prioritized recommendations that influence retention strategy, roadmap investment, and operational optimization
• Apply AI techniques — including NLP, LLM integrations, and predictive models — to automate feedback classification, improve signal detection, and reduce time-to-insight
• Maintain governed analytics environments across Qualtrics, Snowflake, Power BI, Tableau, and related systems to ensure secure, scalable enterprise intelligence

Skills

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering
• 6+ years of progressive experience in advanced analytics, customer intelligence, enterprise BI, or CX measurement roles within SaaS or complex customer environments
• Demonstrated experience designing and governing scoring frameworks, driver analysis models, or prioritization methodologies tied to measurable revenue and retention outcomes
• Proven experience building and deploying predictive models (e.g., churn probability, renewal risk, expansion propensity) that informed real business decisions
• Demonstrated experience operationalizing AI- and LLM-driven analytics within enterprise decision workflows — not just experimentation or prototype analysis
• Experience applying NLP and machine learning techniques to large-scale unstructured customer feedback and behavioral datasets
• Experience partnering with Data Science, Engineering, Product, and Finance to move models from concept to production deployment
• Strong experience designing executive-facing data visualizations and translating statistical findings into prioritized, decision-ready recommendations
• Demonstrated ability to connect customer experience and analytical outputs directly to GRR, CPO, CSAT, operational efficiency, and cost-to-serve metrics
• Experience operating as a senior-level individual contributor, setting analytical standards and influencing cross-functional direction without direct authority

Qualifications

Must Haves

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering
• 6+ years of progressive experience in advanced analytics, customer intelligence, enterprise BI, or CX measurement roles within SaaS or complex customer environments
• Demonstrated experience designing and governing scoring frameworks, driver analysis models, or prioritization methodologies tied to measurable revenue and retention outcomes
• Proven experience building and deploying predictive models (e.g., churn probability, renewal risk, expansion propensity) that informed real business decisions
• Demonstrated experience operationalizing AI- and LLM-driven analytics within enterprise decision workflows — not just experimentation or prototype analysis
• Experience applying NLP and machine learning techniques to large-scale unstructured customer feedback and behavioral datasets
• Experience partnering with Data Science, Engineering, Product, and Finance to move models from concept to production deployment
• Strong experience designing executive-facing data visualizations and translating statistical findings into prioritized, decision-ready recommendations
• Demonstrated ability to connect customer experience and analytical outputs directly to GRR, CPO, CSAT, operational efficiency, and cost-to-serve metrics
• Experience operating as a senior-level individual contributor, setting analytical standards and influencing cross-functional direction without direct authority

Benefits

• Paid time off
• Paid parental leave
• Private medical
• Life, and disability insurance