Model Validation & Implementation Analyst
Job Description:
- 2+ years of experience in model implementation, validation, or risk analytics, preferably within the banking or credit card industry.
- Hands-on experience with statistical modeling, machine learning algorithms, and data analysis.
- Familiarity with credit risk modeling, fraud detection models, or customer behavior analytics is a plus.
- Proficiency in programming languages such as Python, data analysis and model implementation.
- Experience with database management systems (e.g., SQL) and data visualization tools (e.g., Tableau, Power BI).
- Strong understanding of statistical and machine learning concepts, including regression, classification, clustering, and neural networks.
- Strong problem-solving skills with the ability to analyze complex datasets and extract meaningful insights.
- Experience with statistical testing, hypothesis testing, and data validation techniques.
- Perform independent validation of models, including stress testing, back-testing, and sensitivity analysis, to assess the accuracy, reliability, and stability of models.
- Evaluate the assumptions, methodologies, and data inputs used in model development and ensure they comply with regulatory standards and best practices (e.g., Basel, SR11-7).
- Collaborate with data scientists and model developers to implement statistical models for credit risk assessment, fraud detection, and customer behavior analysis.
- Ensure accurate and efficient deployment of models into production systems, working closely with IT and engineering teams to integrate models into banking platforms.
- Ensure all models comply with regulatory requirements, such as Basel, OCC, Federal Reserve, and other applicable regulations.
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