AI Value Partner, Customer Analytics

Role Overview

Cresta is expanding its Customer Success organization with a dedicated analytics function focused on customer value realization. As an AI Value Partner, Customer Analytics, you’ll be the technical engine behind measuring and storytelling customer impact—designing experiments, analyzing conversational and operational data, and building dashboards that quantify Cresta’s value.

You’ll sit within the Customer Success organization and partner closely with Customer Success Managers, Sales, Product, and Engineering. Your work will power ROI discussions, pilots, QBRs and ongoing strategic customer engagements.

This role is ideal for someone early in their data science career who enjoys hands-on analytics, problem-solving, and turning ambiguous business questions into clear, actionable insights.

Key Responsibilities

Customer Analytics & Insight Generation

• Conduct exploratory data analysis (EDA) across conversational, operational, and performance datasets
• Translate ambiguous business questions into structured analytical problems
• Analyze how workflow, behavior, and product usage changes translate into business value

Experimentation & Pilot Measurement

• Design and analyze A/B tests and quasi-experiments to measure Cresta’s impact
• Establish baselines, metrics, and measurement plans for pilots
• Ensure results are statistically rigorous and easy for non-technical stakeholders to understand
• Build reusable templates and frameworks for consistent experimentation
• Work directly with customer to guide them towards our ideal experiment setup

Dashboards, Reporting & Automation

• Build and maintain dashboards tracking customer ROI
• Develop Python and SQL tools to improve repeatability, accuracy, and scalability
• Create standardized reporting packages for pilots, QBRs, and renewals

Modeling & Advanced Analytics

• Develop custom statistical or ML models (e.g., segmentation, predictive scoring, lightweight NLP)
• Maintain reusable modeling pipelines for value insights and roadmap analysis
• Partner with Engineering when guidance or productionization support is needed

Cross-Functional Collaboration

• Translate analyses into clear business and financial narratives
• Support CSMs with data and insights for strategic QBRs
• Partner with Product and Engineering on metrics, data availability, and analytics enhancements

Required Qualifications

• 1–3 years of experience in a data-focused role or relevant academic experience