Senior Quantitative Risk Analyst - Hybrid (Modeling & ML)

CIBC; Toronto; Hybrid; CAD 90,000 - 130,000; Full time

Job summary

CIBC in Toronto is seeking a Sr. Quantitative Analyst to support Quantitative Risk Modelling with model development, monitoring, governance, assessment, and consultation. You will use Databricks, Python, SAS, and other modelling software to execute the performance monitoring process for various risk models, reporting to the Sr.

Manager. The role offers a hybrid work arrangement with 1–3 days on-site, while other days may be remote, supporting analytics, ML, and SAS/Python expertise in credit and

Qualifications

• Experience in data analytics focused role.
• Proficiency with SQL, Python, PySpark, Databricks, SAS.
• Degree in Analytics, Statistics or Mathematics.

Responsibilities

• Model Performance Monitoring – day-to-day model operations, monitoring, dashboards and reports to track predictive model performance.
• Models and Scorecards Development – contribute to development of new models/scorecards for credit, AML, and fraud risk.
• Value-Added Quantitative Analysis – support development and implementation of models and communicate risk information.

Skills

Advanced analytics

Machine Learning

SQL

Python

PySpark

Databricks

SAS

Risk modelling

Education

Bachelor's degree in Analytics/Statistics/Mathematics

Tools

Databricks

Python

SQL

PySpark

SAS

Job description

CIBC in Toronto is seeking a Sr. Quantitative Analyst to support Quantitative Risk Modelling with model development, monitoring, governance, assessment, and consultation. You will use Databricks, Python, SAS, and other modelling software to execute the performance monitoring process for various risk models, reporting to the Sr.

Manager. The role offers a hybrid work arrangement with 1–3 days on-site, while other days may be remote, supporting analytics, ML, and SAS/Python expertise in credit and