Data Scientist - ML, Causal Inference & Experiments

Amazon Science; Seattle (WA); On-site; USD 136,000 - 184,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Science in Seattle seeks a Data Scientist for the Prime Video Science team to design and analyze experiments, evaluate AI systems, and turn model results into business insights. You will work closely with cross-functional teams, apply causal inference and statistical modeling, and communicate findings to technical and business stakeholders.

The role requires a self-starter attitude, strong attention to detail, and the ability to thrive in a fast-paced environment.

Qualifications

• Master's degree or above in statistics, data science, or a quantitative field.
• 2+ years of data scientist experience.
• 2+ years of SQL, Python or statistical software experience.
• 2+ years of ML, statistical modeling, data mining, and analytics experience.
• 1+ years of working with or evaluating AI systems.

Responsibilities

• Design and analyze randomized experiments to validate models and measure impact.
• Build evaluations and benchmarks for AI systems and define performance criteria.
• Run deep-dive analyses on model outputs and customer behavior to tell a data story.
• Apply statistical modeling and causal inference to answer business questions.
• Communicate findings to business, finance, engineering, and science stakeholders.

Skills

Experiment design

Statistical modeling

Causal inference

Data analysis

Communication

SQL

Python

Education

Master's degree or above in a quantitative field

Ph.D. in a quantitative field (preferred)

Tools

SQL

Python

R

SAS

Matlab

Job description

Amazon Science in Seattle seeks a Data Scientist for the Prime Video Science team to design and analyze experiments, evaluate AI systems, and turn model results into business insights. You will work closely with cross-functional teams, apply causal inference and statistical modeling, and communicate findings to technical and business stakeholders.

The role requires a self-starter attitude, strong attention to detail, and the ability to thrive in a fast-paced environment.