Causal ML Engineer for A/B Testing & Uplift

Snap Inc.; Bellevue (WA); On-site; USD 209,000 - 313,000; Full time

Job summary

Snap Inc. is seeking a Machine Learning Engineer to design and deliver causal ML solutions that inform product and policy decisions. You will build models for uplift and heterogeneous treatment effects, and productionize them within scalable infrastructure.

You will work with data scientists and engineers to analyze experiments, interpret results, and steer experimentation strategies while maintaining rigorous methodological standards.

Qualifications

• Bachelor’s degree in computer science, statistics, economics, or related field or equivalent practical experience.
• 5+ years of post-Bachelor’s experience in machine learning with causal inference or experimentation; or advanced degree plus related experience.
• Demonstrated experience building models to support product decision-making through causal techniques.
• Experience designing and analyzing online experiments (A/B tests) and leveraging causal ML in production systems.

Responsibilities

• Design and build models that quantify causal impact and drive value for users, advertisers, and the business.
• Develop and productionize causal machine learning solutions using observational and experimental data.
• Design, analyze, and interpret A/B tests and quasi-experiments with partners.
• Evaluate tradeoffs between model complexity, bias/variance, scalability, and interpretability.
• Conduct code reviews and maintain scalable, maintainable infrastructure.
• Contribute to rapid iteration cycles while ensuring methodological rigor.

Skills

Causal inference

A/B testing

Python

Experimentation infra

Communication/mentorship

Education

Bachelor's degree in CS/Statistics/Economics

Tools

CausalML

EconML

DoWhy

scikit-learn

Job description

Snap Inc. is seeking a Machine Learning Engineer to design and deliver causal ML solutions that inform product and policy decisions. You will build models for uplift and heterogeneous treatment effects, and productionize them within scalable infrastructure.

You will work with data scientists and engineers to analyze experiments, interpret results, and steer experimentation strategies while maintaining rigorous methodological standards.