Amazon Data Scientist GenAI Innovation Center Public Sector Team 

United States, Texas, Arlington 

827784533

This position requires that the candidate selected be a US Citizen.Key job responsibilities
The primary responsibilities of this role are to:
Design, develop, and evaluate innovative ML models to solve diverse challenges and opportunities across industries.A day in the life2. Share your latest experiment results or challenges with other scientists on the team.4. Attend or a deliver a tech talk to highlight a project you or a team mate just completed.6. Meet with customer stakeholders to demonstrate the latest progress on their problem.About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the 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.Mentorship & 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.Work/Life Balance

- 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
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing, neural deep learning methods and/or machine learning
- Bachelor's degree and 8 years of experience or Master's degree and 4 years of experience

- PhD or Masters degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field
- Practical experience in solving complex problems in an applied environment
- Hands on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer)