AVP, Credit Model Development

Role Summary/Purpose:

We are looking for an AVP, Credit Model Development candidate who is curious and passionate about developing innovative solutions and has experience in big data environments, computer programming, Hadoop, Spark, Python, etc.  The successful candidate will have excellent communication & project management skills, strong model development experience and good understanding of model risk.

Our Way of Working

We’re proud to offer you choice and flexibility. At Synchrony, our way of working allows you to have the option to work from home, near one of our Hubs or come into one of our offices. Occasionally you may be required to commute to our nearest office for in person engagement activities such as business or team meetings, training and culture events.

Essential 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

Qualifications/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.)

Desired Characteristics:

• 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.