Senior Applied Scientist - Predictive Scoring, AWS Marketing Science
Core
Design and deploy high-impact deep learning models for predictive lead scoring, customer segmentation, and adaptive recommendations to drive AWS marketing outcomes.
Role type
Senior Applied Scientist (Predictive Scoring & Deep Learning)
Builds
Production-grade ML systems for customer acquisition, conversion, and retention strategies.
Domain
Cloud Services (AWS) / Marketing Science / Deep Learning
Deliverable
production ML models
Required skills
Deep learning, representation learning, survival analysis, graph networks, transformer architectures, neural deep learning methods, statistical analysis, experimental design, causal inference, counterfactual analysis, MLOps, SQL/Spark for big data processing, Python, PyTorch, TensorFlow
Preferred skills
LLM fine-tuning, federated learning, automated feature engineering, siamese networks, efficient transformer architectures, session-based recommendations, two-tower architectures, churn modeling, patent/publication experience
Technologies
AWS SageMaker, MLflow, PyTorch, TensorFlow, Java, C++, Python, Spark
Responsibilities
Design predictive lead scoring models; Architect end-to-end ML pipelines; Publish research and file patents; Conduct A/B testing and causal inference; Collaborate with MLOps engineers; Mentor junior scientists; Define evaluation frameworks tied to business outcomes.
Seniority
Senior, hands-on IC with research leadership