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Amazon Data Scientist, SMGS Security Escalations in Seattle, Washington

Description

This role with partner with the existing Security Experts to validate that security controls are enabled throughout the lifecycle of traditional Machine Learning and Generative AI phases of model development. The security controls will be defined from the early experimentation phases to model fine-tuning to model deployment and ongoing operational governance.

As a data scientist, you have deep and broad experience as an ML practitioner. You interface directly with customers to understand and identify their challenges that can be addressed by Generative AI. You build secure solutions that can scale to the size of the problem at hand and guide customers through your rigorous evaluation process. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

Key job responsibilities

• Lead the development of security guidance on the use of AI/ML, particularly generative AI • Design, develop, and evaluate innovative ML models to solve diverse challenges and opportunities across industries. • Collaborate with security experts to validate and recommend security controls applicable for all phases of AI/ML/Gen AI development lifecycle • Design, build, test, and help deploy ML and generative AI solutions that have measurable business and customer impact in security. • Interact with internal and external customers to understand their business problems and help them in implementation of their generative AI and ML solutions • Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder • Create detailed security documentation of solutions using reference architectures and implementation/configuration guidance • Collaborate with AI/ML peers to research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges • Provide customer and market feedback to Service and Engineering teams to help define product direction • Work with a cross section of AI experts to develop solutions that will be piloted with customers for their production workloads

A day in the life

  1. Team with a GenAI strategist to understand a customer problem and provide guidance on how and whether GenAI can help address the issue. 2. Share your latest experiment results or challenges with other scientists on the team. 3. Collaborate on a blog post to share the results and methods used in your most recent customer success. 4. Attend or a deliver a tech talk to highlight a project you or a team mate just completed. 5. Provide feedback to your team during a code review. 6. Meet with customer stakeholders to demonstrate the latest progress on their problem

About the team

AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services. 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 Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship 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. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our Amazon offices.

We are open to hiring candidates to work out of one of the following locations:

Austin, TX, USA | Herndon, VA, USA | Nashville, TN, USA | Seattle, WA, USA

Basic Qualifications

  • 1+ 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

  • 1+ 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

Preferred Qualifications

  • Experience in Python, Perl, or another scripting language

  • Experience in a ML or data scientist role with a large technology company

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125,500/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

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