Sr. Applied Scientist, Amazon B2B Payments and Lending, Credit Science

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

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.

• Apply advanced data mining, machine learning and other analytical/scientific techniques to create ML models and support Credit Management processes
• Source, incorporate, and analyze alternative credit data to drive innovation
• Own production model (real time and batch) , conduct code review and model monitoring to insist high bar of operating efficiencies and excellence and ensure high performant on the models
• Collaborate effectively with Credit Strategy, Operations, Product, data and engineering teams in ABPL to underwrite new customers and manage portfolio risk
• You will be responsible for researching as well as educating the business, product, marketing and product teams on the implementation of the models and enable strategic decision making.
• Understand business and product strategies, goals and objectives. Make recommendations for new techniques/strategies to improve customer outcomes.

A day in the life

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.

• Master's Degree in a quantitative field (Statistics, Mathematics, Computer Science, Machine Learning or equivalent)
• 5+ years experience in a science role, applying ML to solve complex problems for large-scale applications
• 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- Ph.D in a quantitative field (Statistics, Mathematics, Computer Science, Machine Learning or Equivalent)
• 10+ years of practical experience applying ML to solve complex problems ;
• 3+ years experience in credit underwriting or related work in financial services domain
• Project management experience for working on cross-functional projects
• Experience in develop and apply Large Language Models (LLM) to solve complex problems for large-scale applications
• Successful record of developing junior members from academia/industry
• 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 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.

If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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.