Senior ML Engineer, Causal Inference (Level 5)

Snap Inc.; United States; Hybrid; USD 178,000 - 313,000; Full time

Job summary

Snap Inc. is seeking a Machine Learning Engineer focused on causal inference to design and productionize models that quantify causal impact and optimize decision-making for users, advertisers, and the business.

You will develop causal ML solutions using observational and experimental data, analyze A/B tests, and collaborate with product and engineering teams to shape experimentation strategies, while balancing model complexity and scalability.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 5+ years of post-Bachelor's ML experience with causal inference or experimentation.
• Experience designing online experiments and leveraging causal ML in production.

Responsibilities

• Design and build models that quantify causal impact and optimize decision-making.
• Develop and productionize causal ML solutions using observational and experimental data.
• Analyze and interpret A/B tests and quasi-experiments with product/engineering partners.
• Evaluate tradeoffs between model complexity, bias/variance, scalability, and interpretability.
• Contribute to scalable, maintainable experiment infrastructure and reviews.

Skills

Causal inference

A/B testing

Python

Experimentation

Education

Bachelor’s degree in CS/Statistics/Economics or equivalent

5+ years ML experience in causal inference

Tools

Pandas

NumPy

scikit-learn

CausalML

EconML

Job description

Snap Inc. is seeking a Machine Learning Engineer focused on causal inference to design and productionize models that quantify causal impact and optimize decision-making for users, advertisers, and the business.

You will develop causal ML solutions using observational and experimental data, analyze A/B tests, and collaborate with product and engineering teams to shape experimentation strategies, while balancing model complexity and scalability.