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Amazon Associate Data Scientist Global Services Security 
United States, Kansas 
756966786

16.09.2024
DESCRIPTION

Key job responsibilities* Eagerly explore data - answering questions posed by our security and business teams
* Implement machine learning and statistical methods to solve specific business problems utilizing code
* Build reporting tools to provide insights and metrics which track model performance and explain variance
* Communicate results and recommendations both verbally and in writing. Educate our business partners about our solutions and potential opportunities
* Seek partnerships with peer AI/ML scientists to further develop your data science skills and a body of work that builds trust among colleagues
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Why AWS
Work/Life BalanceMentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

BASIC QUALIFICATIONS

- Bachelor's degree or higher in computer science, engineering, math, statistics, data analytics or operations research
- 1+ years of data scientist or similar role involving data extraction, analysis, ML or statistical modeling, and communication of results
- 2+ years data querying (e.g., SQL or Hadoop) and scripting language (e.g., Python)
- 1+ years experience with a machine learning toolkit (e.g., SciKit-Learn, Amazon SageMaker, PyTorch)


PREFERRED QUALIFICATIONS

- Master's degree in computer science, engineering, math, statistics
- Hands-on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer)
- Experience working with Large Language Models (LLMs) including prompt engineering, vector databases, and retrieval augmented generation