Developer- Python, Risk Models

FP Inc.

Toronto
Contract
Hybrid
C$65 - C$83
Advanced Python DevelopmentGoogle Cloud Platform (GCP) & Data EngineeringFinancial Risk Modeling Technology (Basel III/IFRS9)

Role Overview

As a Senior Software Engineer within the Retail Risk Analytics Engineering (RRAE) team, you will play a pivotal role in modernising model platforms for one of Canada’s top five banks. This high-visibility role involves implementing regulatory and non-regulatory initiatives, specifically focusing on Basel III and IFRS9 credit risk model technology. You will work within a fast-paced Google Cloud Platform (GCP) environment to deliver robust solutions that meet the needs of Global Risk Management and various enterprise stakeholders.

Key Responsibilities

  • Development & Architecture: Write high-quality, scalable Python code leveraging Google Cloud Native technologies, following best practices for software architecture and clean coding.
  • Optimisation & Quality Assurance: Continually optimise and simplify existing codebases, perform rigorous code reviews, and ensure all deliverables meet stringent quality and performance standards.
  • Documentation: Create and maintain comprehensive technical documentation, including architectural diagrams and flowcharts, to ensure long-term maintainability of systems that impact multiple business lines.
  • Stakeholder Collaboration: Work closely with Risk Models, Analytics, and Regulatory Capital teams to translate complex business requirements into technical solutions.

Required Skills and Qualifications

  • Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field.
  • Minimum 8 years of experience in software development (Java, Python, or C++) with a proven track record of end-to-end application delivery.
  • At least 3 years of recent, hands-on experience specialising in Python programming.
  • Excellent communication skills with the ability to analyse problems from multiple perspectives.

Nice-to-Have Qualifications

  • Experience with GCP native tools (BigQuery, DataFlow, Cloud Functions, Pub/Sub) and orchestration via Airflow.
  • Proficiency with data libraries such as Pandas and NumPy.
  • Familiarity with containerisation (Docker, Kubernetes) and CI/CD best practices using Git/Bitbucket.