Senior Pricing Scientist: ML & Causal Optimization

Amazon Science; Seattle (WA); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

RSUs

Health benefits

401(k) matching

Job summary

Amazon Science in Seattle seeks a Sr Applied Scientist to advance pricing optimization initiatives, building transformer-based price prediction models and applying causal ML to measure impact on customer behavior and business outcomes.

The role requires leadership in cross-functional collaboration with product, engineering, and science teams, with a focus on rapid experimentation and scalable deployment of pricing enhancements.

Qualifications

• 4+ years of applied research experience.
• 3+ years building ML models for business.
• PhD or Master's with 6+ years applied research.
• Experience programming in Java, C++, Python.
• Experience with neural deep learning methods.

Responsibilities

• Lead price prediction models using deep learning and transformers.
• Collaborate with product, engineering, and science teams to deploy ML price estimation.
• Design neural network architectures for large-scale price prediction.
• Stay current with advances in DL, probabilistic forecasting, and multi-objective optimization.
• Deliver measurable pricing improvements.

Skills

Applied research

Machine learning

Cross-functional collaboration

Attention to detail

Problem solving

Education

PhD or MS with 6+ years experience

Tools

Java

C++

Python

TensorFlow

Spark

Job description

Amazon Science in Seattle seeks a Sr Applied Scientist to advance pricing optimization initiatives, building transformer-based price prediction models and applying causal ML to measure impact on customer behavior and business outcomes.

The role requires leadership in cross-functional collaboration with product, engineering, and science teams, with a focus on rapid experimentation and scalable deployment of pricing enhancements.