Data Scientist, AI & Causal Inference for Streaming

Amazon; Culver City (CA); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon's Prime Video Science team is seeking a Data Scientist to design experiments, evaluate AI systems, and turn results into actionable insights. You will work on randomized experiments, model evaluation, and data analyses that inform content investments and product decisions.

The role requires strong communication, detail orientation, and ability to operate in a fast-paced, ambiguous environment, with 2+ years in data science and a quantitative degree.

Qualifications

• Master’s degree or higher in a quantitative field.
• 2+ years of data scientist experience.
• 2+ years of SQL, Python or R/SAS/Matlab experience.
• 2+ years of ML, statistical modeling, data mining and analytics techniques experience.
• 1+ years of working with or evaluating AI systems experience.

Responsibilities

• Design and analyze randomized experiments to validate and calibrate models and measure impact of content and product changes.
• Build evaluations and benchmarks for AI systems and define what good looks like for them.
• Run deep-dive analyses on model outputs, experiment results, and customer behavior to surface the story behind the numbers.
• Apply statistical modeling, causal inference, and data analysis to answer business questions and inform major investment decisions.
• Communicate findings to business, finance, engineering, and science stakeholders through clear analyses and docs.

Skills

Strong communication

Statistical modeling

Experiment design

Ambiguity tolerance

Attention to detail

Education

Master’s degree or higher in a quantitative field

Ph.D. in a quantitative field

Tools

SQL

Python

R

SAS

Matlab

Job description

Amazon's Prime Video Science team is seeking a Data Scientist to design experiments, evaluate AI systems, and turn results into actionable insights. You will work on randomized experiments, model evaluation, and data analyses that inform content investments and product decisions.

The role requires strong communication, detail orientation, and ability to operate in a fast-paced, ambiguous environment, with 2+ years in data science and a quantitative degree.