Senior Lead-Scoring ML Scientist

Amazon Web Services (AWS); Austin (TX); On-site; USD 167,000 - 226,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Web Services, Inc. in Austin, TX is seeking a Senior Applied Scientist focused on lead scoring and deep learning to design production-grade models that drive customer segmentation and predictive prioritization.

You will build end-to-end ML pipelines and collaborate with cross-functional teams to translate novel research into scalable systems. The role emphasizes expertise in deep learning, representation learning, and multi-modal data, with opportunities to publish and mentor while

Qualifications

• PhD or master's with 6+ years of applied research in ML.
• 3+ years building ML models for business use.
• Experience with PyTorch or TensorFlow.
• Proficiency in Python and ML frameworks.
• Strong communication with stakeholders.

Responsibilities

• Design and deploy predictive lead scoring models to optimize customer acquisition, conversion, and retention strategies.
• Architect end-to-end ML pipelines for large-scale deep learning models, including data preprocessing, distributed training, and real-time inference.
• Publish research, file patents, and stay ahead of industry trends in marketing science and propensity modeling.
• Collaborate with MLOps to deploy, monitor, and retrain models using AWS SageMaker and MLflow.
• Mentor junior scientists on ML methodology and production best practices.
• Define offline and online evaluation frameworks with business outcome metrics.

Skills

Machine learning modeling

Deep learning

Communication with stakeholders

Experiment design

Python programming

Education

PhD, or Master's degree and 6+ years of applied research experience

Tools

Python

PyTorch

TensorFlow

SQL

Spark

AWS SageMaker

Job description

Amazon Web Services, Inc. in Austin, TX is seeking a Senior Applied Scientist focused on lead scoring and deep learning to design production-grade models that drive customer segmentation and predictive prioritization.

You will build end-to-end ML pipelines and collaborate with cross-functional teams to translate novel research into scalable systems. The role emphasizes expertise in deep learning, representation learning, and multi-modal data, with opportunities to publish and mentor while