AVP – Credit Model Development

AVP – Credit Model Development

Requirements

• Bachelor’s degree in Mathematics/Statistics/Economics/Financial Engineering or other quantitative field with 3+ years of experience in Credit Risk / Financial Industry, or in lieu of a degree, 5+ years of experience in Credit and fraud Risk / Financial industry
• 3+ years of hands-on modeling experience with Credit/Fraud machine learning models
• 3+ years working with large data sets
• Hands on programming skills (SAS/SQL/R/Python etc.)

Responsibilities

• Build and enhance credit risk and fraud risk models.
• Drive development of in-house credit and transaction fraud models, particularly developing scorecard models
• Utilize internal and external data sources and work on big data environment
• Work on data collection, data cleansing, methodology evaluation, model assessment, model refreshment, implementation testing and documentation.
• Maintain comprehensive model documentation
• Support implementation team(s) on model testing process including implementation specifications development, model testing development and execution to ensure model is appropriately implemented and produces output as designed
• Support the Model Owner throughout model lifecycle from model initiation to model retirement, including enhancements / recalibrations
• Present complex items to varied audiences (co-developers, data warehouse / IT managers, as well as executive leadership)
• Maintain the existing credit risk and fraud risk models by improving the documentation, tracking model changes, remediating model risk findings, identifying any gaps in the model, root cause analysis etc.
• Support model validation efforts as well as respond to regulatory or audit request
• Take models through fair lending and Legal approval process and provide insights on model use, model explainability, adverse actions etc.
• Assist in managing model monitoring process, analyzing the root cause of any material shift, optimizing performance metrics and model recalibrations.
• Provide analytical insight on model usage to strategy teams.
• Provide training to other junior team members on technical / modeling methods as needed
• Support model governance for vendor models as needed
• Perform ad-hoc analyses as required

Preferred Qualifications

• Ability to multitask in a face paced environment while influencing and making judgment calls.
• Master’s degree preferred in computer science, mathematics/statistics, economics, finance, engineering, or other quantitative fields.
• Excellent understanding of machine learning modeling methodologies such as gradient boosting, neural network, random forest and other innovate techniques.
• Excellent written and verbal communication skills
• Good understanding of model risk management, credit risk and fraud strategy controls
• Technical proficiency with Python, R, Hadoop, SAS, SQL, etc.
• Quick learner, detail oriented, strong analytical and problem-solving skills.