Fraud ML Model Monitor & Reporting (Hybrid)

CIBC; Toronto; Hybrid; CAD 85,000 - 125,000; Full time

Benefits offered by this job

Competitive salary

Incentive pay

Banking benefits

Benefits program

Pension plan

Employee share purchase plan

Vacation offering

Wellbeing support

MomentMakers

Job summary

CIBC is seeking a Data Scientist, Model Performance Monitoring and Reporting, to monitor fraud-detection models and report findings to US Fraud partners. You will apply SQL and Python to prepare data, assess performance, and communicate insights.

The role involves developing monitoring pipelines and supporting the transition from SAS to Databricks in a hybrid Toronto-based setting. You will collaborate with data scientists and business partners, applying statistical knowledge to interpret

Qualifications

• Strong SQL and Python programming skills with ability to query, prep and analyze data.
• Solid foundation in statistics and model evaluation concepts.
• Understanding of the model lifecycle: development, evaluation, deployment and monitoring.

Responsibilities

• Monitor model performance and report outcomes to business partners.
• Develop reliable monitoring pipelines using SQL, Python; transition SAS to Databricks.
• Interpret monitoring results and connect findings to model development and usage.
• Collaborate with US Fraud partners to understand monitoring needs and communicate findings clearly.
• Contribute to ongoing improvement of monitoring practices with the team.

Skills

SQL

Python

Statistics

Model Monitoring

Data Analysis

Databricks

Machine Learning

Model Development

Education

Statistics/Math/CS degree

Tools

Databricks

Job description

CIBC is seeking a Data Scientist, Model Performance Monitoring and Reporting, to monitor fraud-detection models and report findings to US Fraud partners. You will apply SQL and Python to prepare data, assess performance, and communicate insights.

The role involves developing monitoring pipelines and supporting the transition from SAS to Databricks in a hybrid Toronto-based setting. You will collaborate with data scientists and business partners, applying statistical knowledge to interpret