Data Scientist II: Optimization for Fulfillment

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

Benefits offered by this job

Health insurance

RSUs

Paid time off

Job summary

Amazon is seeking a Data Scientist on the Fulfillment Technologies Science team to design data-driven solutions for the Amazon Fulfillment Network. You will partner with scientists, engineers, PMs, and operations leaders to deploy optimization, simulation and ML approaches at scale.

The role requires strong analytical skills, experience with forecasting and producing production-grade models, and the ability to communicate complex findings to diverse stakeholders across a global network.

Qualifications

• Bachelor's degree or higher in a quantitative field; or related master's degree.
• 3+ years experience with SQL, Python or R/SAS/Matlab for data analysis.
• Experience in forecasting, ML or statistical modeling and presenting results.

Responsibilities

• Design and conduct experiments to evaluate solutions and improve model performance.
• Lead forecasting models from research through production rollout with metrics.
• Develop and deploy production-grade ML/statistical models using Python/SQL.
• Perform large-scale data analyses to uncover insights and inform decisions.
• Translate findings into clear recommendations for technical and non-technical stakeholders.
• Collaborate with scientists, engineers, PMs, and operations leaders across teams.

Skills

SQL

Python

R

Matlab

SAS

Education

Bachelor's degree or higher in a quantitative field

Tools

SQL

Python

R

SAS

Matlab

Job description

Amazon is seeking a Data Scientist on the Fulfillment Technologies Science team to design data-driven solutions for the Amazon Fulfillment Network. You will partner with scientists, engineers, PMs, and operations leaders to deploy optimization, simulation and ML approaches at scale.

The role requires strong analytical skills, experience with forecasting and producing production-grade models, and the ability to communicate complex findings to diverse stakeholders across a global network.