Description If you are excited about applying your science and engineering skills in business problems in the space of risk measurement, quantification, and mitigation, we invite you to consider this Applied Scientist opportunity within Amazon B2B Payment and Lending (ABPL). ABPL is seeking an 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 - Apply advanced machine learning, deep learning and other analytical/scientific techniques to enable and improve Credit Management decisions - Source and assess various structured and unstructured data and leverage automated modeling framework to streamline data evaluation and integration - Spearhead leader to research and adopt State-of-the-Art AI/ML techniques and define the roadmap to revolutionize underwriting models leveraging adaptive modelling methods, Large Language Models(LLM), etc. - Bar-raising the design and implementation of production model pipelines(real time and batch) , lead design and code reviews to insist on high bar of engineering excellence and ensure high performance of the models - Collaborate effectively with Credit Strategy, Operations, Product, data and engineering teams. You will be advising and educating the leadership and stakeholders of the models and 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 As an 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. Basic Qualifications - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - 3+ years of building machine learning models or developing algorithms for business application experience - Experience in solving business problems through machine learning, data mining and statistical algorithms - Experience programming in Java, C++, Python or related language - Experience in patents or publications at top-tier peer-reviewed conferences or journals Preferred Qualifications - Experience implementing algorithms using both toolkits and self-developed code - Experience in investigating, designing, prototyping, and delivering new and innovative system solutions - Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning 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 $136,000/year in our lowest geographic market up to $222,200/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.