Snap Inc. is seeking a Machine Learning Engineer to design and build causal inference models that quantify impact and optimize decisions for users and advertisers.
The role involves productionizing uplift modeling and heterogeneous treatment effect estimation using both observational and experimental data. You will analyze A/B tests, collaborate with product and engineering to shape experimentation strategies, and evaluate tradeoffs between model complexity, bias, variance, and scalability in a
#J-18808-LjbffrCausal ML Engineer - A/B Testing & Impact in northern at Unknown Company
This position is listed as full time and onsite.