DESCRIPTION
If you are excited about applying your science and engineering skills in business problems in the space of Credit management, B2B Financial Service, and Payments, we invite you to consider this Applied Scientist opportunity within Amazon B2B Payments and Lending (ABPL).
ABPL is seeking a Senior Applied Scientist who combines their scientific and technical expertise with business intuition to build flexible, performant, and global solutions for complex financial and risk problems. You will develop and deploy production models to enhance our product features & processes that will delight our customers.
Key job responsibilities
As a Sr. Applied Scientist, you will design and build systems that support financial products. You will work closely with business partners, software and data engineers to build and deploy scalable solutions that deliver exceptional value for our customers. You will utilize intellectual and technical capabilities, problem solving and analytical skills, and excellent communication to deliver customer value. You will partner with product and operations management to launch new, or improve existing, financial products within Amazon.
Responsibilities include:
- Understand business and product strategies, goals and objectives. Make recommendations for new techniques/strategies including GenAI innovations, agentic AI frameworks, and foundation models, and to improve customer experience and business outcomes
- Apply advanced data mining, machine learning, and Generative AI techniques to create AI/ML capabilities and support Credit and Fraud Management
- Source, incorporate, and analyze alternative data to drive innovation, utilizing GenAI and foundation models
- Own production models (real time and batch), conduct code review and model monitoring to insist high bar of operating excellence and ensure high performant models
- Conduct research and educate business, product, marketing and product teams on the implementation of models and GenAI innovations, enabling strategic decision making through AI-powered insights and automation
A day in the life
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan.
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
BASIC QUALIFICATIONS
- Master's degree or equivalent in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- 5+ years experience in a science role, applying AI/ML to solve complex problems for large-scale applications
- Demonstrated fluency with GenAI tools (e.g., LLMs, code assistants) to accelerate model development, feature engineering, and code generation workflows
- Superior analytical skills. Demonstrated ability to identify and solve ambiguous problems
- Demonstrated attention to detail and desire to roll up your sleeves
- Demonstrated ability to operate both strategically and tactically in a high-energy, fast-paced environment. High degree of organization and ability to manage multiple, competing priorities
- Excellent communication (verbal and written) and collaboration skills that enable you to earn trust at all levels
- Proficiency in Python, SQL, or other programming language
- Experience developing machine learning solutions with AWS
PREFERRED QUALIFICATIONS
- Ph.D. in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- 10+ years of practical work applying AI/ML to solve complex problems for large-scale applications experience
- Experience designing and deploying AI-native systems that leverage foundation models, agentic frameworks, and LLM-powered automation
- Experience with leading experienced scientists as well as having a record of developing junior members from academia or industry to a career track in a business environment
- 3+ years experience in credit underwriting or related work in financial services domain
- Project management experience for working on cross-functional projects
- Proven achievements of developing and managing a long-term research vision and portfolio of research initiatives, with algorithms and models that have been successfully integrated in production systems
Amazon is an equal opportunity employer and does not discri