Provide quantitative support throughout the Risk divisions
Development, implementation, and monitoring of quantitative models including those used for expected credit loss estimation
Provide ongoing support for the development, implementation and validation of quantitative and statistical models and tools as well as back testing models
Responsibility for ad-hoc reporting requests for quantitative modeling and the CECL Allowance for Credit Losses estimation

Requirements

Advanced degree in quantitative analytics, economics, finance, statistics, mathematics, engineering, or a related area (PhD preferred)
Minimum 8-10 years’ experience in statistical/econometric modeling with focus on Consumer credit risk
Experience with programming languages commonly used for quantitative modeling, such as SAS, R, Python
Database experience using SQL-based databases
Cloud-based or data-warehouse-as-a-service experience
Some experience with machine-learning and artificial intelligence approaches
Strong analytical, verbal, and written communication skills
Ability to present a professional image
Ability to work in a team environment, to multi-task and be flexible
Experience with Microsoft office products, such as Word, Excel, PowerPoint, and Outlook
A working understanding of both CECL and Basel II frameworks is a plus.
Experience in a cross-functional environment working with portfolio management concepts and constructing and explaining risk models is a plus.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

quantitative modelingstatistical modelingeconometric modelingexpected credit loss estimationmachine learningartificial intelligenceSASRPythonSQL

Soft Skills

analytical skillsverbal communicationwritten communicationteamworkmulti-taskingflexibilityprofessional image

Certifications

PhD in quantitative analyticsPhD in economicsPhD in financePhD in statisticsPhD in mathematicsPhD in engineering