The Data Science Manager will be a key leadership member the Credit team in Amazon Business Payments and Lending. This leader will lead the science team developing best-in-class underwriting systems.
This role presents a significant intellectual, technical, and operational challenge with enormous opportunity for business impact. Amazon is dedicated to building credit/lending services that help small, medium, and large businesses worldwide. We believe we are in a unique position to serve our customers with exceptional value due to our deep understanding and insight into our base coupled with rigorous scientific approach and customer-focused emphasis to building financial products. This leader will be passionate about enabling the growth of small, medium, and large businesses and other to-be-launched segments by removing a critical barrier to deepening their activity on Amazon – access to capital.
This leader will demonstrate high judgment and deep business experience across economic cycles. They will bring proven ability to identify and recommend data-driven solutions, navigating through complex financial and regulatory issues across geographies. This role is highly strategic and will interact with all levels across a broad range of teams and leaders across Amazon. This leader will need to work with our business and product management partners to communicate the properties of their team’s analysis/modeling. This leader owns the multi-year research agenda and prioritization for the team, and ensure that projects meaningful drive results.
Key job responsibilities
· Lead, mentor, and develop a top-performing data science team
· Apply advanced analytics and ML techniques to support Credit Management processes
· Source, incorporate, and analyze alternative credit data to drive innovation
· Own data science team roadmap, balance multiple projects efficiently and achieve goals in a fast-paced, dynamic environment
· Collaborate effectively with Credit Strategy, operation, product teams, and senior management at ABPL to underwrite new customers and manage portfolio risk
· Enhance operating efficiencies and excellence, ensure high performant credit management science models
· Promote a culture of transparency, integrity, and ethical use of data.
We are open to hiring candidates to work out of one of the following locations:
New York, NY, USA | Seattle, WA, USA
- Masters degree in a quantitative field (Statistics, Mathematics, Computer Science, Machine Learning or equivalent)
- 7+ years experience in a data science role, applying ML to solve complex problems for large-scale applications; 3+ years experience in leadership role managing Machine Learning Scientists
- 5+ years experience in credit underwriting or related work in financial services domain
- 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.
- Experience hiring and leading experienced scientists as well as a successful record of developing junior members from academia/industry to a successful career track
- 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
- PhD in a quantitative field (Statistics, Mathematics, Computer Science, or equivalent from a top-tier institution)
- 10+ years of practical experience applying ML to solve complex problems ; 5+ years experience managing Machine Learning Scientists
- 8+ years experience in credit underwriting or related work in financial services domain; experience with B2B/commercial credit management is a plus
- 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
- Experience developing machine learning solutions with AWS
- Experience with big data platforms like Hadoop or Spark, and machine learning frameworks like TensorFlor or Pytorch
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 $140,100/year in our lowest geographic market up to $272,400/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. Applicants should apply via our internal or external career site.