Senior Causal ML Engineer: Uplift & A/B Experimentation

Snapchat; Los Angeles (CA); On-site; USD 178,000 - 313,000; Full time

Benefits offered by this job

Paid parental leave

Comprehensive medical coverage

Emotional and mental health support

Equity in RSUs

Job summary

Snapchat is hiring a Machine Learning Engineer focused on causal inference to design, build, and productionize causal ML models. You will support experimentation strategy and rigorous evaluation of modeling, measurement, and decision-making impact.

Location: Los Angeles, onsite with a 4+ days/week office presence. Compensation includes a salary range and RSU equity, with starting pay negotiable within the range.

Qualifications

• Strong causal inference understanding with modern treatment effect methods.
• Applied data science experience including A/B testing and uplift modeling.
• Proficiency in Python and libraries such as pandas, NumPy, scikit-learn.
• Ability to solve open-ended problems with statistical thinking and engineering pragmatism.
• Excellent communication and mentorship skills.
• Bachelor’s degree in CS, statistics, economics, or related field (or equivalent).
• 5+ years post-Bachelor’s in ML with causal inference/experimentation, or MS+4+ years, or PhD+2 years.
• Experience building causal models to support product decision-making and policy evaluation.
• Experience designing and analyzing online experiments and leveraging causal ML in production systems.

Responsibilities

• Design and building models to quantify causal impact and drive value for users, advertisers, and the business.
• Develop and productionize causal ML solutions such as uplift modeling and heterogeneous treatment effect estimation.
• Design, analyze, and interpret A/B tests and quasi-experiments with product and engineering partners.
• Evaluate tradeoffs across model complexity, bias/variance, scalability, and interpretability.
• Perform code reviews and maintain scalable, maintainable infrastructure.
• Contribute to rapid iteration while ensuring methodological rigor.

Skills

Strong causal inference

Applied data science

Python programming

Statistical thinking

Independent work

Mentorship

Education

Bachelor’s degree in CS, statistics, economics, or related field

Advanced degree (MS/PhD) in a quantitative field

Tools

pandas

NumPy

scikit-learn

CausalM

CausalML

EconML

DoWhy

Job description

Snapchat is hiring a Machine Learning Engineer focused on causal inference to design, build, and productionize causal ML models. You will support experimentation strategy and rigorous evaluation of modeling, measurement, and decision-making impact.

Location: Los Angeles, onsite with a 4+ days/week office presence. Compensation includes a salary range and RSU equity, with starting pay negotiable within the range.