Original listing text, shown exactly as published by the company.
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 environment
Preferred Qualifications
- 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
Success Criteria
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
Compensation for this position includes a Base salary + Bonus + Equity
Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable. Your recruiter can provide further details. In addition, total compensation includes a comprehensive benefits package for you and your family.
We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain.…
