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.
Other responsibilities include:
- 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
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!
- 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 an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit
https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/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.
