Data Analyst

Canadian Imperial Bank of Commerce•Chicago, IL

10d•Hybrid

About The Position

CIBC Bank USA seeks a Data Analyst to validate complex data mapping and transformation logic for financial applications and systems. Drive implementation and performance of analytical models across development, testing, UAT, and production environments. Develop and implement advanced SQL queries and PySpark automation scripts to extract, transform, and validate raw data from diverse source systems. Design and implement advanced transactional models using banking data to assess credit risk, optimize asset-liability management, and support regulatory reporting. Translate business requirements into actionable modeling solutions, deliver insights for executive decision-making, and ensure all outputs meet compliance and audit standards. Participate in stress testing and scenario analysis to enhance financial performance and risk management. Convert raw operational data into dimensional models and data marts to support analytical reporting and business intelligence initiatives.

Requirements

Bachelor’s degree in Computer Science, Electronics Engineering, Management Information Systems, or a related STEM field.
5 years of progressively responsible experience with executing complex data analysis projects in a financial industry setting.
5 years of experience with entity-relationship diagrams, dimensional schema designs, and conceptual, logical, and physical data modeling.
5 years of experience with advanced SQL queries.
3 years of experience with data lineage analysis.
3 years of experience with Python.
3 years of experience with SQL server.
3 years of experience with advanced formulas, pivot tables, and data visualization in Excel.
2 years of experience with statistical analysis.

Nice To Haves

Agile Thinking
Business Requirements Analysis
Communication
Critical Thinking
Domain Knowledge
Operational Efficiency
Problem Solving
Process Design
Python (Programming Language)

Responsibilities

Validate complex data mapping and transformation logic for financial applications and systems.
Drive implementation and performance of analytical models across development, testing, UAT, and production environments.
Develop and implement advanced SQL queries and PySpark automation scripts to extract, transform, and validate raw data from diverse source systems.
Design and implement advanced transactional models using banking data to assess credit risk, optimize asset-liability management, and support regulatory reporting.
Translate business requirements into actionable modeling solutions.
Deliver insights for executive decision-making.
Ensure all outputs meet compliance and audit standards.
Participate in stress testing and scenario analysis to enhance financial performance and risk management.
Convert raw operational data into dimensional models and data marts to support analytical reporting and business intelligence initiatives.