Job Title: Data Scientist II, Model Health & Governance Duration: 6 Months (possibility of extension/conversion) Location: Toronto, ON/ Markham, ON (Hybrid)
Overview
The Model Health Center of Excellence (CoE) is responsible for ensuring models remain compliant, effective, monitored, and sustainable throughout their lifecycle. The team serves as the primary liaison between Business Owners, Model Vendors, Model Validation (MV), Compliance, Model Risk Management (MRM), Technology, and other governance partners to support model onboarding, validation readiness, performance monitoring, remediation, and ongoing model governance activities.
We are seeking a highly motivated Data Scientist III to join the Model Health CoE. This role combines analytics, model monitoring, governance, documentation, and stakeholder management. The successful candidate will represent the First Line of Defense for assigned models and work cross-functionally to ensure models meet business objectives, governance requirements, and regulatory expectations.
Key Responsibilities Model Performance Monitoring & Analytics
Execute ongoing monitoring activities across a portfolio of production models.
Use Python, SQL, Databricks, and PySpark to extract, transform, analyze, and monitor large datasets.
Evaluate model performance, stability, usage, data quality, operational outcomes, and key monitoring metrics.
Investigate model performance issues, monitoring threshold breaches, data anomalies, and emerging risks.
Perform trend analysis and quantitative assessments to support model governance decisions.
Develop monitoring reports, dashboards, and executive-ready presentations for stakeholders.
Model Governance & Validation Support
Act as the primary First Line representative for assigned models during model lifecycle activities.
Support model onboarding, annual model reviews, ongoing validation, model changes, and remediation initiatives.
Prepare and maintain governance documentation including Model Development Reports (MDRs), Monitoring Plans, validation responses, and supporting evidence.
Coordinate responses to Model Validation, Compliance, Audit, and Regulatory inquiries.
Ensure model documentation remains accurate, complete, and audit-ready.
Stakeholder & Vendor Management
Serve as a liaison between Business Owners, Model Vendors, Model Validation, Compliance, Risk, and Technology partners.
Facilitate governance discussions and drive alignment across multiple stakeholder groups.
Review and challenge vendor-provided model documentation, monitoring evidence, and performance reporting.
Coordinate cross-functional activities required to support model implementation, validation, monitoring, and governance objectives.
Track action items and facilitate timely resolution of governance and validation findings.
Process Improvement & Strategic Initiatives
Identify opportunities to improve model monitoring capabilities, governance controls, and reporting processes.
Support regulatory remediation programs and governance transformation initiatives.
Contribute to automation and process efficiencies using Python, SQL, Databricks, and analytical tools.
Support emerging AI and advanced analytics governance activities as required.
MUST-HAVE Hard Skills:
2+ years of experience in analytics, data science, model governance, model risk management, fraud analytics, financial crime analytics, or related fields.
Strong programming skills in Python and SQL.
Hands-on experience working with Databricks, PySpark, and large-scale data environments.
Understanding of machine learning and AI model methodologies, including supervised and unsupervised learning techniques, classification and regression models, ensemble methods, anomaly detection, and emerging AI solutions.
SOFT SKILLS:
Ability to communicate technical model concepts to non-technical stakeholders and facilitate discussions between business partners, model vendors, and Model Validation teams.
Strong documentation, presentation, and communication skills.
NICE-TO-HAVE
Experience working with Model Validation, Compliance, Audit, Model Risk Management, or Regulatory partners
Experience working with third-party model vendors and reviewing vendor models
Prior TD, banking or financial institution experience
Degree/Level of Education: Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Risk Management, or a related quantitative discipline.
Years of Overall Experience: 2+ years of experience
Interview process: 2 steps, virtual or in person, 1 hour
Applicant Notices & Disclaimers
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At SPECTRAFORCE, we are committed to maintaining a workplace that ensures fair compensation and wage transparency in adherence with all applicable state and local laws.The pay rate for this position is C$52.83/hr.
