Research Engineer - Causal AI

About the Company

Alembic is an applied science company solving marketing's hardest problems by proving what actually works. Backed by leading tech luminaries, Alembic builds trusted systems that Fortune 100 companies use to make multimillion-dollar decisions.

Responsibilities

• Design and implement novel approaches to marketing measurement problems
• Build production systems for causal inference that maintain statistical rigor at enterprise scale
• Develop algorithms that are both mathematically sound and computationally efficient
• Collaborate with customers to understand measurement challenges and develop technical solutions
• Create tools and libraries for internal teams and customers to leverage advanced analytics
• Document research and implementation decisions for reproducibility

Requirements

• 5+ years developing and shipping research code in production environments
• Strong mathematical background in statistics, probability, optimization, or causal inference
• Proficient Python developer capable of writing production-quality code
• Practical experience applying causal inference methods to real-world problems
• Experience processing and analyzing large, data-intensive datasets
• MS or PhD with significant applied research experience
• Background in econometrics, statistics, or computational social science
• Experience with both Bayesian and frequentist statistical methods

Preferred Qualifications

• Experience in marketing analytics, A/B testing, or measurement domains
• Understanding of ML engineering and MLOps practices
• Published applied research or technical writing
• Experience in consulting or customer-facing technical roles
• Background in operations research or decision sciences
• Familiarity with GPU computing and performance optimization
• Understanding of privacy-preserving analytics and differential privacy