Data Scientist, Transportation Network Planning

Job Category: Technology and IT
Job Type: Full Time
Job Location: USA
Company Name: Amazon

Company Overview
At Amazon, our work is guided by four core principles: a relentless focus on the customer over competitors, a passion for innovation, a commitment to operational excellence, and a dedication to long-term thinking. We thrive on building technologies, inventing new products, and delivering services that make a meaningful difference in people’s lives. We embrace experimentation, make swift decisions, and are unafraid to take risks.

As a company, we combine the scale and reach of a global enterprise with the agility and entrepreneurial spirit of a startup. Across teams—from Amazon Web Services to Alexa—Amazonians are constantly developing breakthrough technologies for customers of all kinds, including shoppers, sellers, content creators, and developers worldwide.

Job Overview

Amazon is seeking a Data Scientist to help optimize and innovate our transportation network through advanced data science solutions. In this role, you’ll develop scalable models and tools to improve network performance, support strategic decision-making, and drive operational efficiency.


Key Responsibilities

  • Design and implement scalable data science solutions to audit and enhance the transportation network

  • Build and execute analytical tools and models to simulate and improve network design

  • Contribute to the strategic planning for network optimization, prioritize initiatives, and align with stakeholder expectations


Basic Qualifications

  • Minimum 1 year of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical software (e.g., R, SAS, MATLAB)

  • At least 2 years of experience as a data scientist, statistician, or quantitative analyst working with large-scale, complex datasets in a technology-driven environment


Preferred Qualifications

  • Proficiency with statistical software and business intelligence tools (e.g., SPSS, SAS, S-PLUS, R)

  • Experience working with clustered data processing tools and frameworks (e.g., Hadoop, Spark, MapReduce, Hive)

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