Amazon
Job ID:
2931945 | Amazon.com Services LLC About Us:
Are you ready to help shape the future of shipping? At Amazon Shipping, we are not just entering the shipping industry; we are revolutionizing it! Our goal is to optimize how billions of packages move worldwide each year. By transforming our fulfillment network into a more dynamic shipping powerhouse, we aim to create an intelligent system that will enhance efficiency, speed, and cost-effectiveness for our entire ecosystem. Join us in building a flywheel where new packages strengthen our network and improve our capabilities. Your Role:
We are looking for a Senior Data Scientist with exceptional skills in statistics, machine learning, and forecasting to join our embedded team. You will collaborate with cross-functional teams—including commercial, product, and tech—to develop innovative cost prediction models for Amazon Shipping's spot channel. Your work will directly impact price discovery, model implementation, and the expansion of our forecasting capabilities into new use cases. This is a unique opportunity to apply your expertise to high-impact challenges within the global shipping landscape. Key Responsibilities: Design and develop advanced forecasting models for shipping costs, customer demand, and transportation capacity. Work collaboratively with other scientists to create dynamic price predictions that maximize capacity utilization. Build and implement robust machine learning models for customer segmentation, profitability maximization, performance outlier identification, and risk prediction. Utilize advanced statistical, machine learning, and analytical techniques to develop scalable business solutions. Partner with product managers, data scientists, and software developers to integrate models into production processes. Communicate complex modeling concepts and results effectively to non-technical business leaders. Explore new opportunities independently to leverage scientific insights for organizational growth. Possibility to expand into areas such as causal analytics, optimization, and simulation. About the Team:
Amazon Shipping's pricing team is dedicated to aligning growth strategies with profitability while enhancing long-term customer value. We delve into various challenges, from strategic support at the CEO level to detailed mathematical experimentation and optimization. If you are passionate about leveraging data for impactful decision-making, this team will be an exciting place for you. Basic Qualifications: 5+ years of experience as a data scientist or in a similar role with hands-on experience in data extraction, analysis, statistical modeling, and effective communication. 5+ years of proficiency in data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS). A Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science; or a Bachelor's degree with 8+ years of relevant professional or military experience. Experience with statistical models, including multinomial logistic regression. Preferred Qualifications: 2+ years of experience in data visualization tools like AWS QuickSight, Tableau, or R Shiny. Experience managing data pipelines. Familiarity with the AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue). Proven ability to work collaboratively with data engineers and business intelligence engineers. Experience collaborating with scientists, economists, software developers, or product managers. Join us in creating the future of shipping at Amazon. We welcome diverse candidates and are committed to maintaining an inclusive workplace. We offer competitive compensation that reflects various geographic markets in the U.S., with a base pay range from $143,300 to $247,600, depending on location and experience. Additional forms of compensation and a comprehensive benefits package are included. This position will remain posted until filled. We encourage applicants to apply through our internal or external career site.
2931945 | Amazon.com Services LLC About Us:
Are you ready to help shape the future of shipping? At Amazon Shipping, we are not just entering the shipping industry; we are revolutionizing it! Our goal is to optimize how billions of packages move worldwide each year. By transforming our fulfillment network into a more dynamic shipping powerhouse, we aim to create an intelligent system that will enhance efficiency, speed, and cost-effectiveness for our entire ecosystem. Join us in building a flywheel where new packages strengthen our network and improve our capabilities. Your Role:
We are looking for a Senior Data Scientist with exceptional skills in statistics, machine learning, and forecasting to join our embedded team. You will collaborate with cross-functional teams—including commercial, product, and tech—to develop innovative cost prediction models for Amazon Shipping's spot channel. Your work will directly impact price discovery, model implementation, and the expansion of our forecasting capabilities into new use cases. This is a unique opportunity to apply your expertise to high-impact challenges within the global shipping landscape. Key Responsibilities: Design and develop advanced forecasting models for shipping costs, customer demand, and transportation capacity. Work collaboratively with other scientists to create dynamic price predictions that maximize capacity utilization. Build and implement robust machine learning models for customer segmentation, profitability maximization, performance outlier identification, and risk prediction. Utilize advanced statistical, machine learning, and analytical techniques to develop scalable business solutions. Partner with product managers, data scientists, and software developers to integrate models into production processes. Communicate complex modeling concepts and results effectively to non-technical business leaders. Explore new opportunities independently to leverage scientific insights for organizational growth. Possibility to expand into areas such as causal analytics, optimization, and simulation. About the Team:
Amazon Shipping's pricing team is dedicated to aligning growth strategies with profitability while enhancing long-term customer value. We delve into various challenges, from strategic support at the CEO level to detailed mathematical experimentation and optimization. If you are passionate about leveraging data for impactful decision-making, this team will be an exciting place for you. Basic Qualifications: 5+ years of experience as a data scientist or in a similar role with hands-on experience in data extraction, analysis, statistical modeling, and effective communication. 5+ years of proficiency in data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS). A Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science; or a Bachelor's degree with 8+ years of relevant professional or military experience. Experience with statistical models, including multinomial logistic regression. Preferred Qualifications: 2+ years of experience in data visualization tools like AWS QuickSight, Tableau, or R Shiny. Experience managing data pipelines. Familiarity with the AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue). Proven ability to work collaboratively with data engineers and business intelligence engineers. Experience collaborating with scientists, economists, software developers, or product managers. Join us in creating the future of shipping at Amazon. We welcome diverse candidates and are committed to maintaining an inclusive workplace. We offer competitive compensation that reflects various geographic markets in the U.S., with a base pay range from $143,300 to $247,600, depending on location and experience. Additional forms of compensation and a comprehensive benefits package are included. This position will remain posted until filled. We encourage applicants to apply through our internal or external career site.