Senior Research Scientist — Transportation Optimization

Amazon Science; Bellevue (WA); On-site; USD 159,000 - 215,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Science in Bellevue, WA is seeking a Sr. Research Scientist to design novel mathematical models for the Middle Mile transportation network.

You will confront scientifically complex problems in planning, scheduling, and operations, and advance methods in OR, ML, and simulation to productionize solutions. You will own the scientific agenda, guide ambiguous problems from formulation to production-grade models, mentor other scientists, and influence engineering and leadership across teams,

Qualifications

• PhD or Master’s + 5+ years quantitative field research experience.
• Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive.
• Experience communicating qualitative research methods and findings to non-qualitative researchers.

Responsibilities

• Invent and design new models and algorithms for transportation network planning, scheduling, and labor optimization.
• Frame ambiguous business problems into tractable scientific formulations and distinguish novel research needs.
• Extend the state of the art in OR, ML, and stochastic/discrete-event simulation as required.
• Lead production-grade model delivery from concept to deployment with engineering partners.

Skills

Operations research

Machine learning

Stochastic modeling

Simulation

Education

PhD in a quantitative field

Master's degree in a quantitative field

Tools

AWS

Hadoop

Spark

Pig

Hive

Python

Java

C++

Job description

Amazon Science in Bellevue, WA is seeking a Sr. Research Scientist to design novel mathematical models for the Middle Mile transportation network.

You will confront scientifically complex problems in planning, scheduling, and operations, and advance methods in OR, ML, and simulation to productionize solutions. You will own the scientific agenda, guide ambiguous problems from formulation to production-grade models, mentor other scientists, and influence engineering and leadership across teams,