Banking Quant Data Modeler

Key Skills

Analytical and Problem solving, Data Analytics, Data Mining, Data Modeling, Large data sets, Microsoft Office suites, Microsoft-Excel, Python Programming, R Programming, SAS, SQL, Stata, Statistical modeling

Job Description

The successful candidate will join our 25 person data modeling group where your collaboration and contribution directly impacts the success of our company. The position will focus on commercial bank risk models but all team members receive exposure to models across multiple areas of the bank. This role will provide you with the opportunity to innovate, explore and build solutions using emerging technologies. You will develop and apply statistics, artificial intelligence, machine learning, and deep learning to various business problems in loss prevention. The nature of our business creates a data environment where our quantitative analysts combine art and science to build models. Team members excel in using multiple regression analysis techniques such as Linear and Logistics combined with SAS, R, and SQL. Join a collaborative team that consists of highly experienced and degreed professionals who are encouraged to be build strong knowledge and deep experience across business data models.

Primary responsibilities include:

• Analyze credit risk valuation models, correlations, concentrations, rating migrations, and risk contributions.
• Work with business line partners in embedding and socializing these models and support them with on-going requests.
• Work with the independent model validation team internally to get models approved after development work is complete
• Analyze portfolios on consumer lending side to look at trends to support applications models built for
• Maintain large data sets using advance statistical/modeling tools and willing to pull datasets directly from source systems. Work with appropriate parties to resolve or remediate data quality issues.
• Maintain, review, and adhere to organization’s credit policy; verifying the integrity of the underlying data; constant monitoring and validation of the underlying theories and methodologies.
• Support implementation of models development, including third party vendor solution tools for credit risk
• Prepare any ad-hoc risk quantification projects at the request of management
• Participate in peer review sessions and maintain awareness of new advances in credit risk modeling techniques to ensure the application of best practices to CFG credit risk models. Assure quality and leading-edge nature of work by helping to solve problems faced by others

Qualifications

• 5 plus years of experience in financial industry
• Strong understanding of commercial banking and lending products
• Prior experience in loss forecasting in consumer or commercial lending portfolios (consumer preferred)
• Background and knowledge of the FASB CECL, DFAST rules and other banking regulations like Fair lending Act
• Understanding of compliance and implications of FDIC, OCC, FRB regulatory frameworks as well as U.S. and International accounting standards
• Strong knowledge of statistical software packages; previous experience in data mining, demonstrated experience / expertise in problem solving Extensive understanding of relational databases and ability to effectively utilize statistical software – SAS, Stata, R and Python

Education:

• PhD or Master’s degree in Economics/ Statistics/ Finance/ Physics/ Mathematics preferred

Hours and Work Schedule

Hours per Week: 40

Work Schedule: Monday-Friday