Staff Engineer – Experimentation Team
Core
Build the statistical engine and adaptive experimentation systems that power A/B testing and feature optimization for engineering teams.
Role type
Staff Engineer (Applied Statistics & ML)
Builds
Warehouse-native analysis pipelines, contextual bandits, and adaptive allocation systems.
Domain
SaaS / Data Science / Platform Engineering
Deliverable
production ML models
Required skills
Applied statistics (hypothesis testing, sequential analysis, CUPED, power analysis), Adaptive experimentation ML (contextual bandits, Thompson sampling, Bayesian optimization), Backend systems architecture, Warehouse-agnostic system design, Go/Python, Event-driven architectures, Cloud infrastructure (AWS/GCP), Technical leadership
Preferred skills
Experience with Snowflake/Databricks/Redshift/BigQuery, RL-based allocation, Statistical validity in system design
Technologies
Go, Python, Snowflake, Databricks, Redshift, BigQuery, AWS, GCP
Responsibilities
Build the experimentation statistical engine ensuring statistical correctness; Design warehouse-native experimentation running inside customer data warehouses; Lead adaptive experimentation systems including contextual bandits; Drive the platform roadmap with product and data science; Mentor engineers and raise the team's bar for statistical rigor; Own operational excellence including monitoring and incident response
Seniority
Staff, hands-on IC with significant mentorship and architectural influence
