Research Engineer - Causal AI
Core
Design and implement novel approaches to marketing measurement problems, shipping production systems for causal inference that maintain statistical rigor at enterprise scale.
Role type
Senior Applied Scientist (Causal AI)
Builds
Production systems for causal inference and advanced analytics tools for Fortune 100 customers
Domain
Marketing analytics, causal inference, econometrics
Deliverable
production ML models
Required skills
Causal inference, statistics, probability, optimization, Python (production-quality), data-intensive systems, research-to-production translation
Preferred skills
Bayesian and frequentist statistical methods, ML engineering, MLOps, GPU computing, privacy-preserving analytics
Technologies
Python, NVIDIA DGX clusters
Responsibilities
Design and implement novel approaches to marketing measurement problems, Build production systems for causal inference, Develop algorithms that are mathematically sound and computationally efficient, Collaborate with customers to understand measurement challenges, Create tools and libraries for advanced analytics, Document research and implementation decisions
Seniority
Senior, hands-on IC
