AI Value Partner, Customer Analytics

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.

• 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

• 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

• 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

• 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

• 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

• 1–3 years of experience in a data-focused role or relevant academic experience
• Strong proficiency in SQL and experience working with large datasets
• Proficiency in Python (Pandas, NumPy, scikit-learn)
• Solid understanding of statistics, hypothesis testing, and experimental design
• Experience building dashboards in tools such as Hex, Looker, Tableau, or similar
• Strong communication skills with non-technical stakeholders
• Comfort working in a fast-paced, cross-functional environment

• Experience with conversational data (call transcripts, chats) or text analytics
• Familiarity with causal inference, uplift modeling, or A/B testing frameworks
• Exposure to customer-facing analytics or support roles
• Experience with cloud data stacks (Snowflake, Redshift, etc.)
• Basic NLP or classification experience related to agent behavior or customer intent

Within 6–9 months, a successful hire will have:

• Built dashboards and reporting foundations used across Customer Success
• Implemented standardized pilot measurement and experimentation approaches
• Supported strategic customer analyses that improved renewals or expansion confidence
• Created scripts and automations that significantly reduce manual analysis
• Earned trust as the go-to analytics partner for Customer Success