First Citizens
Senior Risk Analyst - Fraud Model Validation
First Citizens, Raleigh, North Carolina, United States, 27601
Overview
This is a remote role that may be hired in several markets across the United States.This Senior Risk Analyst position is within First Citizens Bank’s Model Risk Management (MRM) team, with a primary focus on conducting validations of the Bank's fraud models. Our Financial Crimes and Compliance (FC&C) model inventory encompasses a diverse range of models, including both machine learning and rules-based systems. To provide an effective challenge, subject matter expertise is essential. A successful candidate must possess strong knowledge of AI/ML and have a thorough understanding of the workflow of a transaction or an application entry/submission to filing of a claim.Responsibilities
Conduct independent model validations to ensure fraud models align with business objectives and design objectives. Verify that models are performing as expected. Identify potential limitations, which includes assessing potential impact.Write detailed model validation reports that present the results from executing a thoughtful and thorough model validation plan.Communicate the model validation findings to model owners, senior management, and regulatory agencies as required.Perform annual reviews and review the ongoing monitoring reports to ensure that the models are performing as intended.Interact with all key stakeholders including model users, model owners, vendors, Model Risk Governance, and other Validators throughout the model lifecycle including validation, ongoing performance evaluation.Suggest enhancements to the existing fraud validation process including Validation templates, ongoing monitoring of models, automation of repetitive tasks.You may be asked to help guide junior team members on model validations.Qualifications
Bachelor's Degree and 4 years of experience in Risk management, or financial analysis, or statistical modeling OR High School Diploma or GED and 8 years of experience in Risk management, or financial analysis, or statistical modeling.Preferred Qualifications:Advanced degree (master’s or Ph.D.) in a quantitative field (e.g., Data Science, Operations Research, Finance, Applied Statistics, or a related quantitative discipline).Minimum 7+ years of experience in model development and implementation or model validation within the financial industry. Minimum 5+ years of fraud analytics experience with software (such as Python, SAS, R).Experience developing or validating fraud models (including card transaction models, wire transactions, check processing, account opening, customer verification, etc.)Well-versed with various performance metrics and the use cases for each, including Kolmogorov-Smirnov, Value Detection Rate, Incident Detection Rate, Area Under Curve, Population Stability Index, Character Stability Index, Precision, Recall, False Positive Ratio, etc.Experience maintaining or validating vendor developed models.Good writers of technical reports.Strong analytical skills and ability to find patterns in transactional data.Advanced programming skills in Python, SQL, SAS, or R.Experience using SQL to pull data from enterprise warehouse databases.Experience developing and/or validating AI/ML models and rule-based models.Exceptional understanding of the banking industry and business lines.Experience communicating validation standards and technical concepts to key stakeholders.Good understanding of federal guidance related to model risk management (SR 11-7, OCC 2011-12).
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This is a remote role that may be hired in several markets across the United States.This Senior Risk Analyst position is within First Citizens Bank’s Model Risk Management (MRM) team, with a primary focus on conducting validations of the Bank's fraud models. Our Financial Crimes and Compliance (FC&C) model inventory encompasses a diverse range of models, including both machine learning and rules-based systems. To provide an effective challenge, subject matter expertise is essential. A successful candidate must possess strong knowledge of AI/ML and have a thorough understanding of the workflow of a transaction or an application entry/submission to filing of a claim.Responsibilities
Conduct independent model validations to ensure fraud models align with business objectives and design objectives. Verify that models are performing as expected. Identify potential limitations, which includes assessing potential impact.Write detailed model validation reports that present the results from executing a thoughtful and thorough model validation plan.Communicate the model validation findings to model owners, senior management, and regulatory agencies as required.Perform annual reviews and review the ongoing monitoring reports to ensure that the models are performing as intended.Interact with all key stakeholders including model users, model owners, vendors, Model Risk Governance, and other Validators throughout the model lifecycle including validation, ongoing performance evaluation.Suggest enhancements to the existing fraud validation process including Validation templates, ongoing monitoring of models, automation of repetitive tasks.You may be asked to help guide junior team members on model validations.Qualifications
Bachelor's Degree and 4 years of experience in Risk management, or financial analysis, or statistical modeling OR High School Diploma or GED and 8 years of experience in Risk management, or financial analysis, or statistical modeling.Preferred Qualifications:Advanced degree (master’s or Ph.D.) in a quantitative field (e.g., Data Science, Operations Research, Finance, Applied Statistics, or a related quantitative discipline).Minimum 7+ years of experience in model development and implementation or model validation within the financial industry. Minimum 5+ years of fraud analytics experience with software (such as Python, SAS, R).Experience developing or validating fraud models (including card transaction models, wire transactions, check processing, account opening, customer verification, etc.)Well-versed with various performance metrics and the use cases for each, including Kolmogorov-Smirnov, Value Detection Rate, Incident Detection Rate, Area Under Curve, Population Stability Index, Character Stability Index, Precision, Recall, False Positive Ratio, etc.Experience maintaining or validating vendor developed models.Good writers of technical reports.Strong analytical skills and ability to find patterns in transactional data.Advanced programming skills in Python, SQL, SAS, or R.Experience using SQL to pull data from enterprise warehouse databases.Experience developing and/or validating AI/ML models and rule-based models.Exceptional understanding of the banking industry and business lines.Experience communicating validation standards and technical concepts to key stakeholders.Good understanding of federal guidance related to model risk management (SR 11-7, OCC 2011-12).
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