AI Value Partner, Customer Analytics
Cresta
| Company | Cresta |
| Category | Data & Analytics |
| Location | United States (Remote) |
| Remote | Remote |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 16 Jan 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform combines conversational AI agents, real-time human agent augmentation, and comprehensive conversation intelligence to drive revenue and efficiency gains across every channel. The world’s leading companies, including United Airlines, Cox Communications, and Marriott, use Cresta to power world-class customer experiences every day.
Born from the Stanford AI Lab, Cresta has raised more than $270 million from the world’s leading investors, including a16z, Greylock, and Sequoia. Cresta’s leadership includes some of the leading minds in AI today. Our CEO, Ping Wu , founded and led Google's Contact Center AI and Vertex AI platforms before joining Cresta to build the future of AI-driven customer experiences.
Over the next few years, AI is going to redefine how people all over the world interact with businesses every day. Come build that future at Cresta.
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
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 envir
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