Applied Scientist
Core
Design, develop, and deploy Causal Inference and AIML solutions to optimize marketing channels, estimate lifetime value, and improve customer acquisition and engagement for Apple Services.
Role type
Senior Applied Scientist (Causal Inference & Marketing Analytics)
Builds
Scalable Causal Inference products, observational testing frameworks, and counterfactual modeling systems
Domain
Consumer Technology / Marketing Analytics / Causal Inference
Deliverable
production ML models
Required skills
Causal Inference techniques (diff-in-diff, synthetic control, propensity score matching), Generative AI, Marketing Mix modeling, Python, SQL, Spark, MLOps, cloud platforms
Preferred skills
PhD in Statistics/Economics/ML, Generative AI for productivity, business acumen for translating complex models
Technologies
Python, R, SQL, Java, C++, Spark, Docker, Generative AI frameworks
Responsibilities
Engineer end-to-end scalable Causal Inference products; analyze large-scale data for predictive methods and quantitative modeling; collaborate with product and engineering teams to deliver technical solutions; stay abreast of AIML research advancements; champion software engineering best practices and MLOps
Seniority
Senior, hands-on IC
