- Develop and implement credit risk scoring models for personal loan origination using traditional and alternate datasets, including cash flow.
- Analyze diverse datasets to identify trends and patterns that may impact credit risk incorporating structured and unstructured data sources.
- Collaborate with cross-functional teams including data engineers, business analysts, and stakeholders to gather requirements and ensure alignment with business objectives.
- Conduct thorough model validation and performance monitoring to ensure accuracy and effectiveness across multiple data streams.
- Stay current with industry best practices, emerging trends, and regulatory requirements related to credit risk modeling, particularly in alternative data usage.
- Communicate findings and insights to technical and non-technical stakeholders in a clear and concise manner, emphasizing the incorporation of alternative datasets.
- Support model deployment and provide ongoing support for model maintenance and enhancements, particularly in the context of evolving data sources and regulatory landscapes.
- Use ML to segment our customers based on behavior and propensity to engage with our various lending products
- Recommend optimal segmentation strategy to build different models for different consumer segments.
- Work on a modern AI/ML platform.
- Use every dataset at disposal to build a feature store for AI/ML models as well as a customer 360 profile.
- Set up testing infrastructure to test different underwriting and credit strategies for different lending products.
- Conceive, design & monitor risk management strategies to improve business profitability in the areas of underwriting, credit line management, universe expansion and alternative data evaluation for lending.
- 5+ years consumer credit risk experience including building credit scorecards/scoring systems.
- Hands on experience building credit underwriting models and feature engineering.
- Familiarity with bureau data and alternate data is a strong requirement.
- Strong development experience with Python is a must along with ML libraries (pandas, NumPy, scikit learn, TensorFlow)
- Familiarity with H2O, Azure ML and Amazon Services is a plus but not required.
- Strong Experience in SQL
- Ability to thrive in a fast paced, team-oriented environment.
- Master's degree or PhD. (preferred) in a quantitative field such as Mathematics, Statistics, Computer Science, Operations Research, Engineering
- Experience in credit scoring models in consumer personal loans in banks and fintech's preferred.
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Senior AI/ML Credit Risk Modeler - Toronto, Canada - Momentum Financial Services Group
Description
Job Description*Candidates must reside in the GTA area to be considered for this role as they will be required to be in office 3 days a week at the Toronto Corporate Office.
Job Description:
As a Senior Credit Risk AI/ML Scientist you will play a huge role not only with building models across our lending portfolio but also be involved in deploying and monitoring of the models in production.
What you will do:
Skills and Experience:
All your information will be kept confidential according to EEO guidelines.
Additional Information
*Notice to Ontario Applicants - National Money Mart is committed to accommodating applicants with disabilities up to the point of undue hardship during the recruitment, assessment and selection process. If you are selected for an interview, please notify National Money Mart if you require accommodation in respect of the materials or procedures used at any time during this process. If you require accommodation National Money Mart will work with you to determine how to meet your needs.
Note to Internal Applicants: All internal applicants are required to notify current manager regarding interest in applying for this role.