Quantitative Risk Manager at Wilmington Savings Fund Society

Job Description

NewLane Finance is a commercial equipment finance company, serving small and mid-size business nationwide.  Our mantra is "business lending done right", and our strategy is to revolutionize small business lending by employing the latest technology and a motivated workforce to deliver fair and transparent financing solutions to businesses with unmatched levels of speed, convenience, and customer service. Our products and services are offered to the business community primarily through financing programs with equipment manufacturers, distributors, and dealers. NewLane Finance is powered by a $24B financial organization.

NewLane Finance is seeking an individual to lead the credit and risk modeling and analytics function using data to advance credit risk behavior and quantification of these risk and return tradeoffs through the deployment of models and algorithms to optimize such strategies. This critical role will be responsible for providing analytical/quantitative input to develop, implement and monitor the build of complex commercial small busines Expected Default (ED) and Probability of Default (PD) credit default models.

The successful candidate will use their business analysis, process, and quantitative knowledge to ensure business intent is matched with modeling outcome, and document development decisions under SR11‐7 guidelines. In addition to responsibilities on individual modeling projects this role will be expected to work on ad‐hoc projects as needed. Communicating model mechanics and articulating nuances to leadership will be an important aspect of the role. This is a great opportunity for someone who is a modeler/statistician/data analyst/coder (or a combination) with experience in commercial small business credit analysis

Key Responsibilities:

• Construct Credit Decision Scorecards and statistically based credit risk modeling strategies based on quantitative modeling methods (e.g., good / bad definition, performance sample windows, sample size and exclusions). 
• Assist in developing and implementing a framework for data collection, processing and analyzing customer and 3rd party data (e.g., PayNet, D&B, consumer credit bureaus) for implementing credit risk strategies
•  Plan and execute self-driven analytics on large data sets (structured and unstructured data) using next generation technologies, prepare analysis and reports to support discussions on key analytics and model aspects to drive decision making
• Validate credit default rates from portfolio attributes (e.g., delinquencies, EOD, loss curves, dealer performance) and make recommendations on credit model and policies
• Work with sales management on risk-based pricing strategies optimizing dealer conversion rates and profitability.
• Oversight of credit data mart used for reporting and portfolio performance monitoring.
• Supporting ongoing and future projects working with the senior team.
• Ability to create visualizations of data and/or quantitative information for management decisioning
• Support building and enhancing procedures and model documentation in compliance with regulatory guidance as well as the Bank’s model risk policy
• Maintain current/develop new analytical reports and presentations for senior management, executive committees, and regulatory exams

Experience:

• Bachelor's degree in Mathematics/Statistics, Operations Research, Economics, Finance, or other quantitative discipline; or in lieu of a degree eight (8) plus years’ experience in Risk, Finance, Consumer Lending
• Seven (7) plus years of commercial small business credit modeling experience.
• Four (4) plus years of experience in Consumer Lending statistical modeling/analytics, preferably related to ALL and/or Loss Forecasting modeling for credit cards.
• Three (3) plus years in coding with Python, PySpark or other equivalent language within the past Five (5) years

Desired Characteristics:

• Demonstrated experience with SAS and other statistical methods. 
• Proven decision-making role constructing credit models in a regulated environment
• Strong quantitative and analytical skills in statistical analysis and data science best practices
• Strong communication and partnering skills

We offer a dynamic, collaborative team environment with a strong credit risk management culture and opportunities to train in new technologies and complex applications.
 

The successful candidate will receive competitive compensation, excellent benefits including Health, Dental, Vision, 401k) with match, flexible spending, Life Insurance, Short Term and Long-Term Disability Insurance, generous PTO and much more…

NewLane Finance is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, age, protected veteran or disabled status, or genetic information.

NewLane Finance will not be able to provide Relocation or Sponsorship

WSFS Bank is inclusive and supportive of individual needs. If you have a physical or other impairment that might require an accommodation, including technical assistance with the WSFS Bank Careers website or submission process, please contact us via email at

WSFS is an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.