As an Associate in our Risk Analytics and Modeling team, you’ll have the opportunity to apply your quantitative, modeling and analytical skills in a real world environment to develop or validate statistical, financial engineering, and AI/machine learning models in the areas of credit risk, market risk, assets and liabilities management, fraud detection, anti money laundering and other functional modeling and analytics area. 

Job Requirements and Preferences: 
 
Basic Qualifications: 
 
Minimum Degree Required: 
Bachelor Degree 
 
Minimum Years of Experience: 
2 year(s) 
 
Preferred Qualifications: 
 
Preferred Fields of Study: 
Economics, Statistics, Applied Mathematics, Mathematics, Financial Mathematics, Data Processing/Analytics/Science 
 
Additional Educational Preferences: 

Master Degree in Financial Engineering is also preferred. 

Preferred Knowledge/Skills: 

Demonstrates some abilities and/or a proven record of success in the implementation of Advanced Data Analytics and modeling that include: 

• Possessing experience with one or more of the following key programming and data analytics tools: Python, R, SAS; 

• Working knowledge of the following secondary languages and tools is a plus: Java, C& 43;& 43;/C , SQL, Tableau, Alteryx, and Excel Macros / VBA /JS; 

• Displaying understanding of advanced AI/machine learning, statistical/econometric modeling techniques, and financial engineering methods to develop and/or validate models (Masters-level coursework in at least one of these subject areas is preferred); 

• Demonstrating knowledge of the financial services industry; 

• Demonstrating exposure to modeling methodologies in at least one of the following areas: credit risk, market risk, assets and liabilities management, fraud detection, anti money laundering and other functional modeling and analytics areas; and, 

• Displaying knowledge or familiarity with industry financial instrument pricing tools and data sources e.g. Bloomberg, Refinitiv etc.