Manager, Credit Decisioning Systems

Questrade Financial Group•Toronto, ON

23h•CA$110,000 - CA$140,000•Hybrid

About The Position

Questrade Financial Group (QFG) is a financial services company that offers a wide range of services including investment, wealth management, mortgages, and real estate. They utilize cutting-edge technology to enhance financial success and security for Canadians. QFG combines human-centric collaboration with AI-driven innovation to redefine financial services. The ideal candidate will be a catalyst for change, using AI to transform customer experiences and empower teams. The company offers a diverse, inclusive, and hybrid workplace that encourages creativity and curiosity. This specific role, Manager, Credit Decisioning Systems, is responsible for the end-to-end administration, configuration, and performance of Flexiti’s “Buy Now, Pay Later” automated lending platforms. The role involves leading the technical implementation of credit policies, managing data ingestion via SQL and APIs, and overseeing the deployment and monitoring of Machine Learning (ML) models for real-time lending decisions. This position supports the Credit Risk Strategy team in ensuring the effective implementation and continuous monitoring of risk systems, with a focus on data integrity and system performance.

Requirements

Hold a University degree in a quantitative field, Economics, Business, Statistics, Mathematics, Engineering or equivalent
Have 3-5 years of total experience in credit risk, fintech, or banking operations
Have 3+ years of direct experience managing automated decisioning engines
Have 2+ years of experience in a leadership or senior-level role overseeing technical projects or small teams
Have experience managing an Adjudication decisioning platform
Domain Knowledge: understanding of credit risk concepts, lending products, or fraud-related systems
Know Decisioning Platforms: Advanced proficiency in at least one major platform (Provenir, FICO Blaze/Platform,TakTile, Experian PowerCurve, or Zest AI)
Have Analytical Acumen: Strong ability to analyze data, identify patterns, and effectively debug system issues
Have a proactive and agile mindset with a keen ability to identify and contribute to the resolution of technical and process challenges
Have excellent interpersonal skills and a team-oriented approach, capable of working effectively with cross-functional teams and internal/external partners
Possess meticulous attention to detail, in monitoring system performance and ensuring the accuracy of data and strategy implementations
Are proficient in SQL, Python or R, for rule creation, complex data extraction, model integration and data analysis
Have familiarity with JSON/XML for API integration, DataBricks and BigQuery
Are organized and able to work independently and can handle pressure of tight timelines or emergencies

Nice To Haves

Hold a Master’s degree in a quantitative field, Economics, Business, Statistics, Mathematics, Engineering or equivalent

Responsibilities

Assisting in the design, coding, and testing of credit strategies for various lending products and the full credit lifecycle of customers.
Supporting the integration of credit systems with core banking platforms and collaborating with vendors to implement optimal solutions.
Utilizing SQL, Python, BigQuery, and Data Bricks extensively to pull data, monitor strategy migrations, and conduct analytics to debug issues and validate updates within the risk systems.
Monitoring and leveraging real-time reporting mechanisms to ensure correct strategy execution and identifying potential issues promptly.
Assisting in implementing, updating, and maintaining credit models and strategies collaborating with Credit Risk Strategy teams to "productionize" Python/R-based ML models within the decisioning workflow, ensuring proper mapping of variables.
Participating in the process for user testing changes in strategies and models, ensuring accuracy and functionality.
Identifying and suggesting enhancements and opportunities for process optimization and cost reduction within risk systems.
Managing the daily operations of the credit decisioning engine, ensuring 99.9% uptime for real-time application processing.
Designing and maintaining SQL-based ETL processes to load internal and external data (Bureau, KYC, Alt-Data) into the decisioning environment as required.
Establishing dashboards to monitor decisioning latency, and "approval/decline" distributions. Ensuring all system changes comply with OSFI (Canada).
Serving as the primary technical point of contact for platform vendors, managing upgrades, API integrations, and troubleshooting.
Leading User Acceptance Testing (UAT) for all logic changes and managing "Champion/Challenger" A/B testing strategies to optimize portfolio performance.