Senior Causal ML Engineer for Impactful Experimentation

SNAP, Inc.; California; On-site; USD 209,000 - 313,000; Full time

Benefits offered by this job

Equity (RSUs)

Job summary

Snap Inc. is seeking a Machine Learning Engineer to design and productionize causal ML solutions that quantify effects and drive value for users, advertisers, and the business. You will lead experiments, analyze results, and collaborate with product and engineering partners to shape experimentation strategies.

The role requires strong Python skills, expertise in causal inference, and experience deploying models in production. Equity in RSUs is available; office-based collaboration is encouraged.

Qualifications

• Bachelor’s degree in CS, statistics, economics, or related field, or equivalent practical experience.
• 5+ years in ML with causal inference or experimentation; or advanced degrees with required years.
• Proven experience building causal models to support product decisions.
• Experience designing and analyzing online experiments (A/B tests).

Responsibilities

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

Skills

Causal inference

A/B testing

Python

Experimentation infra

Statistical thinking

Cross-functional collab

Communication

Mentorship

Independence

Education

Bachelor’s degree in CS/Statistics/Economics

5+ years ML with causal inference/experimentation

Experience building product decision models

Experience designing online experiments

Tools

CausalML

EconML

DoWhy

scikit-learn

Job description

Snap Inc. is seeking a Machine Learning Engineer to design and productionize causal ML solutions that quantify effects and drive value for users, advertisers, and the business. You will lead experiments, analyze results, and collaborate with product and engineering partners to shape experimentation strategies.

The role requires strong Python skills, expertise in causal inference, and experience deploying models in production. Equity in RSUs is available; office-based collaboration is encouraged.