Amazon Senior Data Scientist Generative AI Innovation Center 

United Kingdom, England, London 

225658620

You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.We’re looking for ML Data Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.Key job responsibilities
As an ML Data Scientist, you will* Collaborate with ML scientist and architects to Research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges* Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
* Provide customer and market feedback to Product and Engineering teams to help define product direction
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 AWSWork/Life BalanceInclusive Team CultureMentorship 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.

- PhD degree in Computer Science, or related technical, math, or scientific field
- Proven knowledge of Generative AI and hands-on experience of building applications with large foundation models
- Proven knowledge of AWS platform and tools
- Hands-on experience of building ML solutions on AWS
- High impact thought leadership in AI/ML space through blog posts, public presentations, social media visibility, or publications.