Applied Scientist , AWS Marketing Science
Core
Build and improve machine learning models for lead scoring, customer segmentation, and account prioritization to drive AWS marketing engagement and conversion strategies.
Role type
Applied Scientist II (Marketing Science)
Builds
Production-grade ML models and measurement systems for marketing attribution, propensity scoring, and next-best-action.
Domain
Cloud computing marketing, predictive analytics, deep learning
Deliverable
production ML models
Required skills
deep learning modeling, survival analysis, graph networks, transformer architectures, multi-modal modeling, causal inference, A/B testing, Java, C++, Python, algorithms and data structures, numerical optimization, data mining, parallel and distributed computing
Preferred skills
professional software development experience
Technologies
AWS SageMaker, MLflow
Responsibilities
Develop and maintain ML pipeline components for data preprocessing, feature engineering, model training, and inference integration; Conduct offline and online evaluation frameworks to track business outcomes; Partner with MLOps engineers on model deployment, monitoring, and retraining; Contribute to internal and external research including technical publications and patent filings.
Seniority
Mid-level, hands-on IC
