Specialist, Scoring and Modeling

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Position: Specialist, Scoring and Modeling
Location: Downtown Toronto or London, ON
Job Type: Permanent - 3 days onsite

We are seeking a Specialist, Scoring & Modeling to join our client in the Financial Services space. Reporting directly to the Director of Scoring & Modeling.

In this role, you will take ownership of model development initiatives and play a key role in preparing data, building statistical models, supporting model implementation, and overseeing ongoing model performance.

What you’ll be doing:

• Lead end-to-end model development projects—primarily credit risk scorecards—using techniques such as decision trees, logistic regression, and various machine learning methods.
• Extract, transform, and analyze raw datasets (primarily using SAS) to deliver timely, high-quality insights for scoring and modeling projects.
• Create and maintain detailed model documentation that aligns with regulatory expectations.
• Support the operational deployment of models by coordinating with cross‑functional teams to ensure accurate and timely implementation.
• Build, maintain, and review monitoring and validation reports, offering insight into model performance for different business applications.
• Act as the main point of contact with external partners (e.g., credit bureaus and modeling consultants) to ensure data and analytical requirements are fulfilled.
• Stay current with emerging statistical approaches, machine learning techniques, and industry best practices.
• Provide technical expertise, guidance, and data‑driven recommendations to leadership from a predictive modeling perspective.
• Communicate key findings and insights effectively to both technical and non‑technical audiences, using visualizations and clear storytelling.

What you’ll need:

• At least 4 years of hands‑on experience in analytics and predictive modeling within financial services, preferably in credit risk.
• Bachelor’s or Master’s degree in a quantitative field such as Statistics, Economics, Mathematics, Engineering, or Actuarial Science.
• Solid understanding of credit risk model development, validation, and monitoring practices.
• Strong foundation in statistical and machine learning methods (e.g., regression, gradient boosting, neural networks, clustering) and the ability to choose the right technique for the problem.
• Proven experience working with data using SAS, SQL, or Python.
• Experience with large datasets, data mining, and data warehouse environments.
• Knowledge of Canadian raw credit bureau data is a significant asset.
• Advanced Excel skills (e.g., pivot tables, index‑match) and familiarity with Access or similar database tools.

Please send your resume in Word format to Bronwyn Massey at bronwyn.massey@quantum-qtr.com.