Data Analyst (3+ years) to support enterprise stress testing and credit risk forecasting using Python-based data workflows- 41570

S I Systems; Toronto; Hybrid; CAD 55,000 - 83,000; Full time

Job summary

S I Systems is seeking a Data Analyst with 3+ years of experience to support enterprise stress testing and credit risk forecasting using Python-based data workflows in a hybrid Toronto environment.

Responsibilities include designing data solutions, optimizing Python notebooks, integrating multiple data sources, and collaborating with risk partners and model developers. The 6-month contract offers exposure to IFRS 9 modelling and production-grade data processing.

Qualifications

• 3+ years of Data Analyst experience with large datasets and complex code processes.
• Strong Python proficiency, including optimizing data-heavy workloads.
• Experience writing clean, maintainable, scalable, and testable code.
• Academic or professional exposure to credit risk modelling (PD/LGD).

Responsibilities

• Design and develop data solutions to integrate new data sources into stress testing platforms.
• Develop and optimize Python-based data extraction, transformation, and consolidation processes.
• Analyze existing code and implement improvements aligned with stress testing methodologies.
• Refactor notebooks and workflows for readability, performance, and scalability.
• Collaborate with risk partners and model developers to validate results and document processes.

Skills

Python

SQL

Data analysis

Code maintainability

Large datasets

Education

Bachelor's degree

Master's degree

Job description

Data Analyst (3+ years) to support enterprise stress testing and credit risk forecasting using Python-based data workflows- 41570

Our financial services client is seeking a Data Analyst (3+ years) to support enterprise stress testing and credit risk forecasting using Python-based data workflows- 41570

Location Address: Hybrid - Toronto – 3 days/week (no fixed days – flexible)

Contract Duration: 6 months (Possibility of extension & conversion to FTE)

Schedule Hours: 8:30am-5pm Monday-Friday; standard 37.5 hrs/week

Story Behind the Need

Business Group & Project: Enterprise Stress Testing's (EST) mandate is to design, develop, and execute the Bank's enterprise-wide stress testing program. The team is responsible for assessing the potential impact of adverse economic and business scenarios on the Bank's credit portfolio and overall financial performance.

The Credit Risk Stress Testing team is seeking a Contract Data Analyst to support the modernization, optimization, and implementation of Python-based stress testing processes. The successful candidate will contribute to credit risk forecasting and scenario analysis initiatives, helping the Bank assess potential credit losses under various economic conditions.

This role will specifically support the FSAM2 (Financial Sponsor / Asset Management) project, a regulatory-driven initiative focused on enhancing the Bank's approach to stress testing and assessing potential credit losses associated with the Financial Sponsor and Asset Management portfolio. The project is currently in its implementation phase, with methodology development nearing completion and technical execution underway.

The Data Analyst will focus on improving the performance of data-intensive Python workflows, refactoring code for scalability and maintainability, and developing new data ingestion and consolidation processes from multiple upstream data sources. The role will also support future phases of the project involving the implementation and integration of newly developed credit risk models.

Team Structure: 8 FTEs organized by portfolio coverage (e.g., Canadian Retail Banking, Business Banking).

Project Status: Phase 2 is currently underway and focused on implementing methodologies into production processes. Phase 2 is expected to continue through April 2027 (the current contract end date), with Phase 3 anticipated to involve broader cross‑functional collaboration and implementation of additional credit risk models. There is potential for extension beyond the initial contract term.

Typical Day in Role:

• Design and develop data solutions to integrate new data sources into existing stress testing platforms and support new stress testing initiatives.
• Develop and enhance Python-based processes to source, transform, validate, and consolidate data from multiple upstream systems.
• Analyze existing codebases and implement changes based on evolving stress testing methodologies and business requirements.
• Optimize the performance of large-scale, data-intensive Python notebooks and workflows.
• Refactor code to improve readability, maintainability, scalability, and efficiency while preserving business logic.
• Ensure outputs are accurate, reliable, and well-documented for downstream analytics, reporting, and modeling purposes.
• Collaborate with internal stakeholders, model developers, and risk partners to gather requirements and validate results.
• Create technical documentation and provide knowledge transfer to support long-term sustainability of solutions.
• Support end-user data processing and calculations through Python-based scripting and automation.
• Gain exposure to IFRS 9 methodologies, stress testing frameworks, and credit risk forecasting processes.

Candidate Value Proposition:

The successful candidate will have the opportunity to contribute to a high-impact regulatory and risk management initiative within bank's Enterprise Stress Testing team.

This role offers valuable exposure to:

• Credit risk analytics and loss forecasting within a leading financial institution.
• Enterprise stress testing methodologies and regulatory reporting practices.
• IFRS 9 modelling and credit loss estimation processes.
• Large-scale data management, automation, and Python development.
• Collaboration with quantitative model developers, risk professionals, and business stakeholders.
• A strategic project with potential for extension beyond the initial contract period.

Candidate Requirements/Must Have Skills:

1) 3+ years’ experience as a Data Analyst, with hands‑on experience working with large datasets and complex code processes (co‑op, internship, or professional experience will be considered).

2) Strong proficiency in Python, with hands‑on experience optimizing data‑heavy workloads

3) Experience applying software development best practices, including writing clean, maintainable, scalable, and testable code

4) Academic or professional experience in credit risk modelling, particularly related to Probability of Default (PD) and/or Loss Given Default (LGD)

Nice-To-Have Skills:

1) Strong SQL skills and experience working with relational or cloud data warehouses

2) Experience moving notebook-based workflows toward more production-ready designs

Education:

Bachelors + Masters required

Successful candidates in the team come from these programs: Master of Financial Risk Management, Master of Mathematical Finance, Master of Management Analytics, Statistics, Data Science

CFA/FRM certifications are an asset

Best VS. Average Candidate:

3+ years’ experience can include internships/co‑ops – looking for a junior type of candidate / fresh grad

Hands‑on experience in credit risk modelling (from academic or work experience) is the priority - Understands key credit risk concepts, including Probability of Default (PD), Loss Given Default (LGD), and stress testing methodologies.

Genuine interest in credit risk domain as a career

Demonstrates strong Python programming and data manipulation capabilities.

2 rounds

1 st technical round– in person Toronto – 1 hour - Interview with a Senior Manager and/or Director, including:

• Python coding and data manipulation exercises.
• Live problem-solving and solutioning discussions.
• Statistical and modeling knowledge assessment.
• Questions related to analytical approaches, data processing, and quantitative concepts.

Required materials will be provided during the interview.

2 nd final behavioral/culture fit interview with HM – Virtual Video Interview

Disclaimer: AI may be used in evaluating candidates. This posting is for an existing vacancy.