Amazon Data Scientist Applied AI Solutions 

United States, Washington, Seattle 

532109221

As a Data Scientist, you will build scalable solutions and models to support our business functions. Leveraging a range of methods including machine learning and simulation, you will explain, quantify, predict and prescribe in support of informing critical business decisions. You will translate business goals into agile, insightful analytics. You will seek to create value for both stakeholders and customers and inform findings in a clear, actionable way to managers and senior leaders.Key job responsibilities
Key job responsibilities
- Use statistical and AI/ML techniques to create the next generation of the tools that inform strategic decision-making at AWS's highest levels- Create predictive models and analytical solutions that provide deep insights into revenue patterns, cost structures, and growth opportunities
- Develop innovative approaches to complex financial problems using advanced statistical methods and machine learning- Drive the adoption of data-driven decision making across Applied AI Solutions
About the team
Diverse Experiences
AWS 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.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

- 2+ years of data scientist experience
- 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 machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment