Overview
This position is within First Citizens Bank's Model Risk Management (MRM) team, with a primary focus on conducting validations for the bank's models used for credit risk rating, marketing, and wealth management. Our team encompasses a diverse range of models, including both traditional statistical models and AI machine learning models.
The analyst will collaborate with validation manager to conduct independent model validations for one or more specific areas based on their background and expertise. The primary objective is to verify that models are performing as expected and aligning with their design objectives and business use cases while identifying potential limitations and assumptions and assessing their potential impact.
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This role provides an excellent opportunity for the analyst to rotate within the team, gaining a comprehensive and holistic understanding of the bank's model risk management framework.
*This position can work remote from anywhere within the United States.
Responsibilities
- Model Inputs Analysis: Apply data analysis techniques to assess the quality, integrity, and appropriateness of data used in the models. Examine data extraction, cleaning, transformation processes, and evaluate data-related assumptions and limitations.
- Model Framework Evaluation: Scrutinize the model design and construction, verifying the suitability of the modeling framework and theory for the intended use. Review model segmentation, variable selection, model testing procedures, and evaluation model assumptions, limitations, and risks.
- Model Code Review: Review model code to ensure correctness, accuracy, and absence of material errors. Collaborate with model developers to address any identified issues.
- Outcomes Analysis: Assess both in-sample and out-of-sample back test results; evaluate sensitivity and scenario testing, and quantitative and business performance metrics.
Qualifications
- Bachelor's Degree and 2 years of experience in Risk Analytics or Analytics OR High School Diploma or GED and 6 years of experience in Risk Analytics or Analytics
- Advanced degree (Master's or Ph.D.) in a quantitative field (e.g., Mathematics, Statistics, Computer Science, Data Science, Finance, Economics, Physics, Engineering, or a related discipline).
- Experience in model development, model validation, or model implementation within the financial industry. Proficiency in statistical methods (e.g., linear regression, logistic regression, survival analysis, ARIMA), AI/machine learning techniques (e.g., Random Forest, XGboost, Clustering, Neural Network, NLP, Image Recognition) and programming languages (e.g., Python, R, SAS, SQL).
- Strong understanding of regulatory requirements: SR 11-7/ FIL-22-2017 and SR 15-19.
- Excellent problem-solving skills, attention to detail, and ability to work both independently and collaboratively within a team.
- Excellent written and verbal communication skills.