Senior Applied Scientist, Decision Intelligence

Amazon; Seattle (WA); On-site; USD 167,000 - 226,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Job summary

Amazon in Seattle, WA is hiring Senior Applied Scientist to design, build, and deploy ML/AI models powering our decision intelligence platform. You will work at the intersection of causal inference, time-series forecasting, anomaly detection, and LLM-based reasoning to solve real operational problems with measurable business impact.

You will own end-to-end from research to production, design experiments, and translate complex results into actionable insights for senior leaders.

Qualifications

• PhD in ML, Stats, CS, OR, or related field (or MS + 4 years applied science experience).
• 3+ years of building ML models for business applications.
• Strong expertise in at least two of: causal inference, time-series forecasting, anomaly detection, NLP/LLMs.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn, statsmodels).
• Experience deploying ML models to production.
• Track record of publications or equivalent internal research contributions.

Responsibilities

• Design, build, and deploy ML/AI models powering the decision intelligence platform.
• Develop causal inference, time-series forecasting, anomaly detection, and LLM-based reasoning models.
• Build RAG systems and prompting architectures for grounding outputs in data.
• Design experiments and causal methods to measure true impact of interventions.
• Own end-to-end research-to-production lifecycle from deployment to monitoring.

Skills

3+ years ML development

Python

Causal inference

Production ML deployment

Education

PhD in ML/Statistics/CS/OR

Tools

PyTorch

TensorFlow

scikit-learn

statsmodels

Job description

Amazon in Seattle, WA is hiring Senior Applied Scientist to design, build, and deploy ML/AI models powering our decision intelligence platform. You will work at the intersection of causal inference, time-series forecasting, anomaly detection, and LLM-based reasoning to solve real operational problems with measurable business impact.

You will own end-to-end from research to production, design experiments, and translate complex results into actionable insights for senior leaders.