Senior Data Analyst with SAS, SQL and Python experience to support a unsecured lending project with one of our major banking clients- 39504

Senior Data Analyst with SAS, SQL and Python experience to support a unsecured lending project with one of our major banking clients- 39504

Location Address: Hybrid - Toronto - 3 days/week (Monday, Wednesday, Thursday), may increase to 4

Contract Duration: 6 months

Schedule Hours: 9am-5pm Monday-Friday; standard 37.5 hrs/week

Story Behind the Need

Business group: Unsecured Lending - responsible for the credit strategy for credit cards, including origination and account‑management strategies. The team has 18 members and is in the process of expanding to approximately 20 through the hiring of 3 full‑time roles and 1 contractor.

Project: No single project focus. This role supports business‑as‑usual (BAU) activities and the Hiring Manager’s portfolio by working with credit card and unsecured line of credit (ULOC) performance and application data.

Typical Day in Role:

- Perform data pulls, data preparation, and validation using SQL, SAS, Python, or similar tools

- Support ad‑hoc analysis for credit card and ULOC portfolio trends

- Ensure data accuracy and consistency across analytical outputs

- Design, build, and maintain data visualizations, dashboards, and reporting using Power BI, Tableau, Excel, or Python

- Translate analytical outputs into clear visuals for stakeholders

- Maintain and progressively take ownership of recurring reports and dashboards

- Support monitoring of credit risk KPIs such as approval rates, delinquency, loss rates, utilization, vintage performance

- Assist with credit risk strategy monitoring or evaluation under guidance

- Collaborate closely with credit risk, analytics, and strategy teams

- Communicate analytical findings clearly and concisely

- Majority of the role is data manipulation, analysis, and visualization.

Candidate Value Proposition:

The successful candidate will gain meaningful exposure to the unsecured lending and credit domain. Join a high‑performing, purpose‑driven analytics team shaping Canada’s retail unsecured lending strategy. Work directly with real credit card and ULOC performance data. Build and enhance dashboards, recurring reports, and analytical insights used by business and risk leaders. Grow into ownership of defined reporting or strategy components. Use modern analytics tooling including SQL, Python, SAS, Power BI/Tableau, and risk analytics frameworks.

Candidate Requirements/Must Have Skills:

1) 8+ years’ experience in data analysis, visualization and reporting

2) 5+ years’ experience with large datasets using SAS, SQL, Python

3) Experience with data visualization & reporting tools: Power BI, Excel

Nice-To-Have Skills:

1) Retail credit risk knowledge, especially credit cards and ULOC

2) Experience with consumer credit performance data & risk metrics

3) Experience working in financial services analytics environments

Education:

Bachelor’s in relevant field

Best VS. Average Candidate:

The ideal candidate demonstrates strong analytical skills using SAS and SQL, combined with familiarity in credit risk data and the capability to turn data into meaningful insights. Experience with retail banking products-especially credit cards and ULOC-will significantly differentiate top candidates.

Candidate Review & Selection - Interview Process

1-2 rounds, in person at 44 King Street

Approximately 1 hour per round

Interviews with Hiring Manager, two Directors, and potentially a VP

Includes technical skill assessment and a short live case study

Candidate will be given material and asked to walk through their solution approach

Hiring Manager’s availability to interview: Wednesday Feb 18th, Thursday Feb 19th, Monday Feb 23rd