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Role overview

This contract opportunity is for a Data Analyst supporting a newly created Credit Card and Unsecured Lending (CCUL) Engagement Squad in Toronto, Ontario. The assignment runs for 3 months and is based in the Greater Toronto Area with a hybrid work arrangement. The squad focuses on engaging current customers rather than new acquisition, with work centered on initiatives such as Select Pay, balance transfers, and credit limit increases.

What you will do

Act as the primary analytics partner for the squad and contribute in daily standups.
Assess credit card data, determine whether requested data points are feasible, and size potential opportunities.
Build dashboards and streamline recurring tasks using Excel and Power BI.
Provide practical recommendations and insights for marketing initiatives to business and marketing stakeholders.
Work through large datasets to uncover patterns, opportunities, and customer behavior trends with a customer-first lens.
Partner with business and marketing teams to define target audiences and estimate opportunity size.
Deliver pre-sizing, segmentation, and response forecasting to support campaign planning and efficiency.
Improve customer and channel allocation using behavioral, preference, and historical performance data.
Help define KPIs and benchmarks, and create reporting that tracks campaign results.
Run pre- and post-campaign deep dives that go beyond offer acceptance to evaluate utilization, stickiness, acquisition cost, and revenue impact.
Present findings and recommendations clearly to stakeholders and maintain alignment across teams.
Collaborate in agile squads with marketing, execution, and business partners to identify ways to improve the customer experience.
Investigate and profile data sources, assess backend data critically, and translate findings into useful business insight.
Perform SQL development and data manipulation as required.
Support automation and dashboard creation through Power BI and Excel.
Contribute to modernization efforts, including movement from Db2/SAS toward GCP and Python-based analytics.

Required experience and background

At least 8 years of experience in data analysis with the ability to prepare and present reports for cross-functional audiences.
At least 8 years of experience working with large datasets and relational databases, including advanced SQL capability.
At least 5 years of hands-on experience with Power BI.
At least 2 years of recent experience using Python.
A quantitative academic background such as statistics, applied mathematics, economics, or computer science.

Preferred experience

Exposure to banking products.
Experience with Google Cloud Platform.
Background in targeted lead generation, campaign execution, or segmentation.

Working style and soft skills

Strong communication and collaboration skills.
Self-driven approach with solid quantitative ability and strong attention to detail.
Comfort with problem solving and curiosity about customer behavior.
Analytical thinking and the ability to turn data into action.

Interview process

The selection process is expected to include 1 to 2 in-person interviews with the hiring manager, each lasting about 1 hour and focused on experience review and scenario-based questions.

Additional information

The recruitment team may use artificial intelligence tools during screening, but applications will also be reviewed by a human recruiter to support a fair and complete evaluation.

Engagement details

This is a 3 month contract role. The posting does not specify salary, number of openings, start date, or application deadline.

Data Analyst