First Citizens Bank · 12 hours ago

Senior Risk Analyst - Fraud Model Validation

New York, United States

Full-time

Remote

Senior Level

$105K/yr - $150K/yr

7+ years exp

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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 on-going 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, on-going monitoring of models, automation of repetitive tasks.

You may be asked to help guide junior team members on model validations.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Risk ManagementStatistical ModelingFraud AnalyticsModel ValidationPythonSASRSQLAI/ML ModelsBanking Industry KnowledgeModel Risk Management GuidanceTechnical Writing

Required

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

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).

Preferred

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).