Job Description and Requirements
The Senior Credit Risk Modeling Analyst will develop, validate, and enhance credit risk models to support decision-making, profitability, and compliance.The Analyst will analyze complex datasets, assess portfolio performance, and forecast credit risks to optimize lending and institution strategies.
Essential Functions and Responsibilities:
- Utilize risk modeling techniques to identify, quantify, and forecast potential credit risk and opportunities for the institution.
- Develop and maintain expertise in the fields of risk quantification and modeling to support both internal and external stakeholders.
- Collaborate with stakeholders to understand product characteristics used for modeling while assisting in communication and education of current and expected risk exposures.
- Make recommendations to management on current and future strategies and profitability projections.
- Perform other quantitative analysis for institution stakeholders as needed.
- Leverage expertise to foster and expand collective knowledge within the team.
- Gather and analyze pertinent data to create or strengthen models that forecast risk exposure and help make informed business decisions.
- Continuously monitor the economic and business environments to update models as new data becomes available.
- Define, document, and summarize methodologies, assumptions, and results of risk models and prepare reports for management.
- Act as a liaison between lending and IT to assist in the aggregation and organization of institutional data for the use in models and reporting.
- All other duties as assigned (note: essential functions and responsibilities may change, or new ones may be assigned at any time with or without notice).
Requirements:
- Master’s degree in finance, statistics or other quantitative field
- Minimum 3 years of job-related experience or 6+ years of job-related experience in lieu of Master’s degree
- Strong analytical, mathematics, organizational, and planning skills
- Ability to articulate complex theories, concepts, methodologies, and findings in a non-technical manner to a non-technical audience
- Innovative self-starter with ability to meet deadlines, work independently, and think outside the box
- Excellent interpersonal skills, with a desire to pursue best practices in a challenging team environment
- Proficient to advanced knowledge of statistical modeling and other quantitative techniques including, but not limited to, linear & non-linear regression, optimization, simulation, time-series analysis, probability theory, survival analysis, and value-at-risk
- Knowledgeable of modeling systems and/or computer programming languages used for modeling (e.g. python & R)
- Ability to complete multiple projects and meet deadlines
- Capable of working on assignments with minimal assistance
All qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status.