Amazon Science

Description 
 
Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you? 
 
We are looking for a Data Scientist who will be responsible to develop scientific solutions to optimize our fulfillment strategy across multiple regions of the world (EU, JP, IN and more), to maximize our Customer Experience and minimize our cost and carbon footprint. 
 
You will partner with the worldwide scientific community to help design the optimal fulfillment strategy for Amazon. You will also collaborate with technical teams to develop optimization tools for network flow planning and execution systems. Finally, you will also work with business and operational stakeholders to influence their strategy and gather inputs to solve problems. 
 
To be successful in the role, you will need deep analytical skills and a strong scientific background. The role also requires excellent communication skills, and an ability to influence across business functions at different levels. 
 
You will work in a fast-paced environment that requires you to be detail-oriented and comfortable in working with technical, business and technical teams. 
 
Key job responsibilities 
 

* Design and develop mathematical models to optimize inventory placement and product flows.
* Design and develop statistical and optimization models for planning Supply Chain under uncertainty.
* Manage several, high impact projects simultaneously.
* Consult and collaborate with business and technical stakeholders across multiple teams to define new opportunities to optimize our Supply Chain.
* Communicate data-driven insights and recommendations to diverse senior stakeholders through technical and/or business papers.
* Leverage LLMs to improve explainability of our optimization solutions and drive engagement from supply chain planners across the world. 
 
 

Basic Qualifications 
 


* Experience working as a Data Scientist
* Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent)
* Experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance
* Experience applying theoretical models in an applied environment 
 
 

Preferred Qualifications 
 


* Experience in Python, Perl, or another scripting language
* Experience in a ML or data scientist role with a large technology company 
 
 

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy\_page) to know more about how we collect, use and transfer the personal data of our candidates. 
 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Data

Amazon

Python

Network

Customer Care

Community management

Project management

Software Development

Machine Learning

Communications

Data analytics

Scripting language

Security software

MATLAB

Perl

Analysis

System security

Support

Data Science

Statistical model

Supply chain management

Statistical Programming

Mathematical Modelling

Inventory management

Flow

Technical Writing

Team collaboration

Data Scientist, network planning optimization world wide, Supply Chain Optimization Technology