Data Scientist, SCOT Forecasting and Labs - CIV Team

Description

Are you seeking an environment where you can drive innovation? Do you want to apply inference, advanced statistical modeling and techniques to solve world's most challenging problems in? Do you want to play a crucial role in the future of Amazon's Retail business? Do you want to be a part of a journey that develops a new technology from scratch for answering critical business question in Amazon Retail?

Every time an Amazon customer makes a purchase, a number of systems are involved : these systems help optimize acquisition, enable a number of purchase options, ensure great , store products so they are available for fast delivery, and minimize package frustration. The Technology (SCOT) Group develops and manages these systems. We are central to Amazon customers' ability to find what they want and get it when they want it.

The Consumer Instock Value (CIV) team within Amazon's Supply Chain Optimization Technology (SCOT) Group develops and manages systems that estimate the long-term impact of inventory availability and delivery speed changes at the product level. Our estimates are crucial inputs for multiple production systems across Amazon's supply chain planning, helping teams make critical decisions about inventory management, selection, and placement.

Key responsibilities of a Data Scientist in CIV Team include :

Developing new statistical, causal, and machine learning techniques and develop solution prototypes to drive innovation

Working with technical and non-technical customers to design model improvements and communicate results

Collaborating with our dedicated software team to create production implementations for large-scale data analysis

Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business

Presenting research results to our internal research community

Leading training and informational sessions on our science and capabilities

Your contributions will be seen and recognized broadly within Amazon, contributing to the Amazon research corpus and patent portfolio.

Basic Qualifications

3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical / mathematical software (e.g. R, SAS, Matlab, etc.) experience

3+ years of data scientist experience

3+ years of machine learning / statistical modeling data analysis tools and techniques, and parameters that affect their performance experience

Bachelor's degree

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 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 for more information. If the country / region you're applying in isn't listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125,500 / year in our lowest geographic market up to $212,800 / year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and / or other benefits. For more information, please visit . This position will remain posted until filled. Applicants should apply via our internal or external career site.