Are you passionate about building data-driven applied science solutions to drive the profitability of the business? Are you excited about solving complex real world problems? Do you have proven analytical capabilities, exceptional communication, project management skills, and the ability to multi-task and thrive in a fast-paced environment? Join us a Senior Applied Scientist to deliver applied science solutions for Amazon Payment Products. Amazon Payment Products team creates and manages a global portfolio of payment products, including co-branded credit cards, instalment financing, etc. Within this team, we are looking for a Senior Applied Scientist who will be responsible for the following:
Key job responsibilities
As a Senior Applied Scientist, you will be responsible for designing and deploying scalable ML, GenAI, Agentic AI solutions that will impact the payments of millions of customers and solve key customer experience issues. You will develop novel deep learning, LLM for task automation, text processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. As the Payment Products organization deals with problems that are directly related to payments of customers, the Senior Applied Scientist role will impact the large product strategy, identify new business opportunities and provides strategic direction, which will be very exciting.- Experience in applied research
- Master's degree, or PhD
- Master's degree, or PhD and 5+ years of practical machine learning experience
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- Experience in leading large-scale, technical or engineering programs with a proven record of thought leadership, business case development, realizing customer benefits, and successful program completion
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Solid understanding of machine learning, deep learning algorithms and computational complexity. Experience in building and productionizing machine learning models for business application.
- Demonstrated strong problem solving and analytical skills with ability to identify and frame technical problems from broad product-level and business-level problem areas.
- Experience in end to end technical architecture, design, deployment and operations for Generative AI/ML platforms and applications. Demonstrated experience with LLM-powered agentic workflow, orchestration, agent customization and evaluation.
- Strong verbal/written communication skills, including an ability to effectively collaborate with both research and technical teams. Demonstrated ability to communicate complex technical problems in simple plain stories.- Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.
- Experience in delivering design solutions for projects of large scope and complexity
- Experience driving scientific agenda and technical strategy in a team, including building consensus on technical approaches and mentoring other scientists to improve their technical capabilities.
- Experience with AWS technologies such as SageMaker, OpenSearch, EC2, Glue, EMR, etc.
- Experience in Applied Scientist role with a large technology company
- Experience working in a fast-paced business environment and demonstrated track record of project delivery for large, cross-functional projects with evolving requirements.
- Credit or risk management experience
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