Sr. Data Scientist, FCGT

- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 5+ years of data scientist experience
- Experience with statistical models e.g. multinomial logistic regression
- Experience working with data engineers and business intelligence engineers collaboratively
- Experience managing data pipelines
- Experience as a leader and mentor on a data science team

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Amazon strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. Amazon's evolution is driven by the spirit of innovation that is part of the company's DNA.

Amazon Seller Services is looking for a Data Scientist to work hands on from concept to delivery on generative AI, statistical analysis, prescriptive and predictive analysis, and machine learning implementation projects. We are looking for a problem solver with strong analytical skills and a solid understanding of statistics & Machine learning algorithm as well as a practical understanding of collecting, assembling, cleaning and setting up disparate data from enterprise systems.



Key job responsibilities
Responsibilities:
Ability to understand a business problem and the available data and identify what statistical or ML techniques can be applied to answer a business question
Given a business problem, estimate solution feasibility and potential approaches based on available data
Understand what data is available, where, and how to pull it together. Work with partner teams where needed to facilitate permissions and acquisition of required data
Quickly prototype solutions and build models to test feasibility of solution approach
Build statistical models/ ML models, train and test them to and drive towards the optimal level of model performance
Improve existing processes with development and implementation of state of the art generative AI models
Work with technology teams to integrate models by wrapping them as services that plug into Amazon's marketplace and fulfillment systems
Work across the spectrum of reporting and data visualization, statistical modeling and supervised learning tools and techniques and apply the right level of solution to the right problem
The problem set covers aspects of detecting fraud and abuse, improving performance, driving lift and adoption, recommend the right upsell to the right audience, cost saving, selection economics and several others.