Data Scientist — AI & Optimization for Warehouse Ops

Amazon; Bellevue (WA); On-site; USD 108,000 - 160,000; Full time

Benefits offered by this job

RSUs

Health insurance

401(k) matching

Job summary

Amazon in Bellevue, WA is seeking a Data Scientist to develop causal, forecasting, and optimization models for North American Operations. You will work with business stakeholders and leverage generative AI to build smarter solutions for our customers.

The role focuses on owning projects from scoping to delivery, collaborating with Operations and Finance teams, and delivering data-driven insights at scale using SQL, Python, and ML techniques.

Qualifications

• 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
• Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in STEM

Responsibilities

• Interfacing with stakeholders to understand business problems and translating these into high and low-level design documents.
• Building machine learning, optimization, and causal inference models that target business-specific challenges.
• Sourcing, cleaning, and analyzing large and complex data sets associated with warehouse operations to provide business-critical insights at scale.
• Leveraging AI-based solutions to drive development and provide nuanced insights into model outcomes.

Skills

SQL

Python

R

SAS

Matlab

Machine learning

AI systems

Education

Master's degree in STEM

PhD in STEM

Tools

SAS

Matlab

Job description

Amazon in Bellevue, WA is seeking a Data Scientist to develop causal, forecasting, and optimization models for North American Operations. You will work with business stakeholders and leverage generative AI to build smarter solutions for our customers.

The role focuses on owning projects from scoping to delivery, collaborating with Operations and Finance teams, and delivering data-driven insights at scale using SQL, Python, and ML techniques.