Senior Lead Scoring & Deep Learning Scientist

Amazon Web Services (AWS); New York (NY); On-site; USD 184,000 - 249,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Web Services, Inc. is seeking a Senior Applied Scientist focused on lead scoring and deep learning to redefine how AWS engages with customers.

You will design scalable models for customer segmentation, adaptive recommendations, and predictive lead/account prioritization, collaborating with cross-functional teams to translate research into production systems. You will mentor junior scientists, define evaluation frameworks, and work with MLOps to streamline deployment, monitoring, and

Qualifications

• 3+ years of building machine learning models for business applications.
• PhD or Master’s with 6+ years of applied research.
• Experience programming in Java, C++, Python or related language.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, or equivalent).
• Real world experience in recommender systems, transformers, or multi-objective tasks.
• Strong background in statistical analysis, experimental design, and SQL/Spark for big data processing.
• Publications or patents in applied ML domains is a plus.

Responsibilities

• Design and deploy predictive lead scoring models to optimize acquisition, conversion, and retention.
• Architect end-to-end ML pipelines for large-scale deep learning models.
• Publish research, file patents, and stay ahead of industry trends.
• Innovate in multi-modal modeling to enhance scoring accuracy.
• Conduct rigorous A/B testing, causal inference, and counterfactual analysis.

Skills

Python

Deep learning

SQL

PyTorch/TensorFlow

Stakeholder communication

Java

C++

Education

PhD

Master's + 6+ years applied research

Tools

AWS SageMaker

MLflow

Spark

Java

C++

Python

Job description

Amazon Web Services, Inc. is seeking a Senior Applied Scientist focused on lead scoring and deep learning to redefine how AWS engages with customers.

You will design scalable models for customer segmentation, adaptive recommendations, and predictive lead/account prioritization, collaborating with cross-functional teams to translate research into production systems. You will mentor junior scientists, define evaluation frameworks, and work with MLOps to streamline deployment, monitoring, and