Credit Risk Analyst

Posted: 50 years618 months2652 weeks18565 days ago

Type: Direct Hire
Compensation: 75-125K (depends on experience)
Level: Executive
Division: Accounting/Finance
Job Description:
 Analyst to help build and create underwriting and collections models, profitability and performance analysis, and develop test and control strategies.
 Use analytical methods including computer and data analysis to build credit and risk models including credit underwriting, product optimization, and operational process analysis
 Demonstrated operational experience using SAS or other standard analytic tools for organizing and solving business analyses
 Demonstrated experience using SQL databases and building reports with Tableau, Crystal reports, or other industry-accepted reporting packages
 Query data for developing and use data for validating the models through financial judgment and statistical tests
 Use data-oriented approach to work with others in solving complex business problems around profitability, marketing, risk, and operational analysis
 Design experiments and use various test and control strategies for collections, marketing, and operations, analyze results, and build predictive models to forecast future outcomes
 Perform data-oriented ‘what if’ and ‘ad-hoc’ analysis to support business strategy optimization in profitability, marketing, risk and operations
Job Qualifications:
 Equivalent Education Level Required: Bachelor’s Degree (Engineering, Science, Mathematics, Economics with emphasis in statistics, strongly Preferred). MS degree preferred. Would benefit from courses in advanced mathematics, computer programming, economics, and operations research.
 Experience Required: 3+ years’ experience in credit, risk management, or fraud analysis (5+ preferred).
 Knowledge Required: Strong written and verbal communication skills, SAS Experience required (SAS Certification preferred), Credit model/underwriting model development (Experience doing this in Specialty Finance preferred), Experience creating linear and logistic regression as well as decision tree models, and basic understanding of statistical principals (p-value, etc.). Comfortable with solving complex problems, working with computers and technology, and using higher level mathematics.
 Travel: As needed, but not expected to be more than 10%.
If you are interested in this position, please send resume/CV and cover letter to