Data Scientist (2+ years of experience) to support model monitoring and governance using Python,

Our banking client is seeking a Data Scientist (2+ years of experience) to support model monitoring and governance using Python, SQL, Databricks, and PySpark

Join a Model Health Center of Excellence supporting consumer reidentification and access management initiatives within a large financial services environment. This role focuses on model monitoring, governance, analytics, validation support, and stakeholder coordination across production models and AI-related initiatives. The position offers exposure to multiple business lines, emerging AI activities, and a broad range of model governance work. This is a backfill opportunity with potential extension based on business needs and performance.

Contract, Toronto, Hybrid, 2 days in office

/ Front Street West or Steeles Ave East Markham,

6 months

Must Haves

• 2+ years in data science, model governance, fraud analytics, financial crime analytics, or related analytics fields
• Strong programming skills in Python and SQL
• Hands-on work with Databricks, PySpark, and large-scale data environments
• Understanding of machine learning and AI model methodologies, including supervised and unsupervised learning, classification and regression models, ensemble methods, and anomaly detection
• Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Risk Management, or a related quantitative discipline

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 banking or financial institution experience

Responsibilities

• Execute ongoing monitoring activities across a portfolio of production models
• Extract, transform, analyze, and monitor large datasets using Python, SQL, Databricks, and PySpark
• Evaluate model performance, stability, usage, data quality, operational outcomes, and monitoring metrics
• Investigate model performance issues, monitoring threshold breaches, data anomalies, and emerging risks
• Prepare and maintain governance documentation including monitoring plans, validation responses, and supporting evidence
• Coordinate responses to Model Validation, Compliance, Audit, and Regulatory inquiries
• Support automation, process efficiencies, and governance transformation initiatives