- 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.
- 2+ 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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AI/ML Credit Risk Modeler - Toronto, Canada - Money Mart Financial Services
Description
Company Description
Momentum Financial Services is a leading provider of financial services in North America. For 40 years, we've been committed to providing financial solutions that meet the evolving needs of consumers and business owners. Backed by a retail network of over 400 locations, we provide access to cash and related products to help our customers achieve their goals.
Our highly skilled workforce puts customers first in everything we do. We serve 2 million people annually with diverse and innovative financial products such as loans, cheque cashing, money transfer and prepaid cards. Through this ever-evolving suite of services, we empower customers to manage their finances and improve their lives. Wherever customers are on their financial journey, Money Mart Financial Services provides solutions.
#Corporate
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 AI/ML 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 :
Qualifications
Skills and Experience:
Additional Information
All your information will be kept confidential according to EEO guidelines.
Additional Information