Pricing Team Charter
Mission
Build the next-generation pricing engine through ML optimization, autonomous pricing, and scalable customer engagement.
Strategic Initiatives
| Initiative |
Status |
Hypothesis |
Key Metric |
| ML Pricing at Scale |
delivery |
ML-optimized pricing (ml_elasticity + LP) improves RA by 5pp and RevPAR by 1-2% |
RA +5pp, RevPAR +1-2% |
| Autopilot 2.0 |
discovery |
RL + override-aware UX + adaptive levers achieves 60%+ RA, sub-second inference |
RA 60%+, sub-second |
| Customer Engagement at Scale |
discovery |
Measurement + segmentation + trust UX increases engaged hotels by 30%, improves Heavy Overrider RA by 10pp |
Engaged +30%, RA +10pp |
Reference
| Initiative |
Purpose |
| Pricing Portfolio Reference |
Historical appendix: absorption map for former PRC-XXX epics, parked items with reactivation criteria |
Team Members
Engineers
| Name |
Role |
Allocation |
Manager |
Status |
Notes |
| Irving Lin |
Tech Lead |
ML Pricing (Eppo, Pricerator), Autopilot 2.0 (adaptive levers) |
Cathy Daves |
Contractor |
50% total allocation |
| Everton Savio Santos Lucas |
C3 |
ML Pricing (experiment infra), Pricerator maintenance |
Cathy Daves |
Encora Contractor |
|
DS/ML (shared ceremonies)
| Name |
Role |
Manager |
Focus |
| Hakim Touati |
ML Architect |
Kartik Yellepeddi |
Training cycle ownership, model deployment |
| Andrew Crane-Droesch |
Principal Data Scientist |
Kartik Yellepeddi |
ml_elasticity, RA model, override populations |
| Cameron Young |
Lead Data Scientist |
Kartik Yellepeddi |
RL model, JAX implementation, simulation |
| Suraj Thapa |
ML Engineer |
Kartik Yellepeddi |
Training pipelines, model serving |
| Prerana Devadhar |
Data Analyst |
Jon |
RA dashboards, IAR metric, ICP scoring |
| Woojong Yi |
Data Analyst |
Jon |
RevPAR analysis, backtesting, experiment metrics |
Product
| Name |
Role |
Manager |
Focus |
| Sujoy Guha |
Product Manager |
Jon |
Strategy, experiment design, multi-price UX, ICP targeting |
