Senior Causal ML Engineer — A/B Testing & Uplift

Snapchat, Inc.; Santa Clarita (CA); On-site; USD 209,000 - 313,000; Full time

Benefits offered by this job

Paid parental leave

Comprehensive medical coverage

RSU equity

Job summary

Snap Inc. is seeking a Machine Learning Engineer to design and productionize causal ML models that quantify impact and guide product decisions. You will work on uplift modeling, heterogeneous treatment effects, and A/B testing, integrating experimental data with production systems.

The role requires strong Python proficiency, experience with causal inference libraries, and the ability to collaborate across cross-functional teams while delivering scalable infrastructure.

Qualifications

• 5+ years of post‑Bachelor’s experience in machine learning, with hands-on experience in causal inference or experimentation
• Experience designing and analyzing online experiments (A/B tests) and leveraging causal ML in production systems
• Demonstrated experience building models to support product decision-making and policy evaluation through causal techniques
• Experience with causal inference libraries such as CausalML, EconML or DoWhy

Responsibilities

• Design and build models that quantify causal impact, optimize decision-making, 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; collaborate with product and engineering partners
• Evaluate tradeoffs between model complexity, bias/variance, scalability, and interpretability
• Conduct code reviews and maintain high engineering standards for scalable infrastructure
• Contribute to rapid iteration cycles while ensuring methodological rigor

Skills

causal inference

A/B testing

Python

data science

experimentation infrastructure

communication

mentorship

cross-functional collaboration

Education

Bachelor’s degree in computer science, statistics, economics, or related field

MS/PhD in quantitative field

Tools

CausalML

EconML

DoWhy

pandas

NumPy

scikit-learn

Job description

Snap Inc. is seeking a Machine Learning Engineer to design and productionize causal ML models that quantify impact and guide product decisions. You will work on uplift modeling, heterogeneous treatment effects, and A/B testing, integrating experimental data with production systems.

The role requires strong Python proficiency, experience with causal inference libraries, and the ability to collaborate across cross-functional teams while delivering scalable infrastructure.