Sr Analyst, Customer Intelligence (AI)

TL;DR

Sr Analyst, Customer Intelligence (AI): Own the analytical foundation behind CX360 by defining and governing scoring frameworks, predictive indicators, and prioritization models that convert multi-source customer signals into decision-grade insight. Focus on productionizing predictive models and applying NLP/LLM-driven analytics to automate feedback classification, improve signal detection, and quantify measurable impact on GRR, retention risk, and cost-to-serve.

Company

hirify.global builds an AI-first cloud compliance platform and enterprise customer intelligence capabilities.

Location

Location: United States

Salary

Salary: $111,300–$215,400 base pay range (varies by state); eligible for an annual bonus.

What you will do

• 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 maintain consistency and transparency.
• Collaborate with Data Science, Architecture, Engineering, and Product to validate data integrity and strengthen insights using predictive modeling and sentiment analysis.
• Build and evolve customer intelligence analytics (segmentation, cohort analysis, driver attribution) tied to retention and efficiency outcomes.
• Quantify financial and operational impact of customer friction using revenue and cost modeling, then translate results into prioritized recommendations.
• Apply AI techniques (NLP, LLM integrations, predictive models) to automate feedback classification and reduce time-to-insight; maintain governed analytics environments across Qualtrics, Snowflake, Power BI, and Tableau.

Requirements

• 6+ years of progressive experience in advanced analytics, customer intelligence, enterprise BI, or CX measurement roles in SaaS or complex customer environments.
• Proven experience designing and governing scoring frameworks, driver analysis models, or prioritization methodologies tied to measurable revenue and retention outcomes.
• 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 only experimentation/prototypes).
• Experience applying NLP and machine learning to large-scale unstructured customer feedback and behavioral datasets.
• Senior-level individual contributor experience influencing cross-functional direction without direct authority.

Culture & Benefits

• AI-first environment: AI embedded in workflows, decision-making, and products.
• Paid time off and paid parental leave; annual bonus eligibility based on individual and company performance.
• Health & wellness benefits vary by location and generally include private medical, life, and disability insurance.
• Inclusive culture with employee-run resource groups and executive sponsorship.

Hiring process

• Interview process to evaluate analytical rigor, scoring/governance experience, and ability to operationalize predictive and AI/LLM-driven analytics.
• Discussion of how experience translates into measurable improvements in retention, efficiency, and customer experience.