Fair Lending Quantitative Analyst

Job description

The Fair Lending Program Office (“the FLPO”) at American Express (“AXP”) invites experienced hires and recent graduates to join our team. The FLPO is responsible for performing quantitative analysis, business process reviews, and other activities in support of AXP's fair lending program. The program promotes AXP's impartiality in lending by assessing the risk of noncompliance with AXP's fair lending principles and applicable fair lending laws and regulations.

The main responsibilities of the fair lending quantitative analyst will be to:
• Independently perform analytical / quantitative projects on fair lending risks throughout the credit card lifecycle, including marketing/solicitation, underwriting, line management, servicing, loss mitigation, and collections;
• Accessing /pulling loan-level data from multiple data sources using SAS and conducting data diagnostics and validity checks;
• Understanding how business policies, procedures and practices foster fair lending;
• Develop and execute linear and logistic regression models to identify fair lending risk in AXP models and strategies;
• Analyze data using statistical modeling software, such as SAS and Excel;
• Summarize and interpret results of quantitative analysis in lay terms for written and oral presentations to management; and
• Support the ongoing development and activities of the FLPO. The learning opportunities provided through a diverse set of projects are complemented by a dynamic work environment and training.

Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.

Desired profile

Successful applicants will have a bachelor's degree in economics, mathematics, statistics, (or related field) and 1-3 years related experience preferred. Other qualifications include:
• Experience with SAS is required including experience in manipulating large datasets and samples;
• Excellent analytical and communication skills, both written and oral;
• Experience developing statistical models including linear and logistic regression;
• High organization skills with the ability to manage and prioritize multiple and concurrent activities and projects in a high energy and dynamic working environment;
• Proven record of success working in a team environment and collaborating with colleagues to achieve desired results; and
• Working knowledge of advanced machine learning methodologies (such as Gradient Boosting Modeling and kNN) is preferred;

American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other status protected by law. Click here to view the "EEO is the Law" poster.