Python Software Developer

Client’s Investments & Capital Markets division is seeking a hands-on Python Software Developer to support its enterprise forecasting platform. In this role, you will develop and enhance core forecasting engines that drive long-term financial projections, strategic decision-making, and critical financial reporting. You will collaborate closely with Financial Planning & Analysis (FP&A) and quantitative teams to improve model accuracy, system performance, and quarterly reporting cycles., Engine & Application Development: Refactor, modernize, and develop core features for financial accounting and forecasting applications to improve scalability, runtime efficiency, and code maintainability.

Production Support & Run Execution: Monitor and support critical quarterly and annual production runs for financial reporting, ensuring output integrity, calculation accuracy, and timely completion.

Quality & Testing: Write clean, modular, production-grade Python code accompanied by automated unit and integration tests (Pytest) to maintain high test coverage.

Troubleshooting & Maintenance: Diagnose and resolve production defects, reduce technical debt, and ensure adherence to clean architecture and software engineering standards.

Cross-Functional Collaboration: Partner with data engineers, infrastructure teams, and FP&A business stakeholders to implement scenario analysis, requirement updates, and platform migrations.

DevOps & Architecture: Support infrastructure upgrades, containerized deployments, shell-based automation scripts, and peer code reviews.

3+ years of hands-on Python software development experience with a Bachelor’s degree in Computer Science or a quantitative discipline, OR

1-2 years of hands-on Python development experience with a Master’s degree in Computer Science, Quantitative Finance, or related technical field.

Databases & Version Control: 1-2 years of experience writing SQL and working with relational databases; strong proficiency with Git in collaborative Agile environments.

Containers & Scripting: 1-2 years of experience with containerization technologies (Docker, Podman, or Kubernetes) and shell scripting for task automation and system troubleshooting.

Testing: 1-2 years of hands-on experience implementing automated testing pipelines using Pytest or related unit-testing frameworks.

Domain Knowledge: Foundational understanding of fixed-income instruments and metrics, including duration, convexity, spread, and option-adjusted spread (OAS).

Communication & Delivery: Strong analytical, critical thinking, and verbal/written communication skills; familiarity with Agile/Scrum delivery.

Preferred Qualifications

Advanced degree (Master’s) in Computer Science, Mathematics, Financial Engineering, or Statistics.

Familiarity with GAAP accounting fundamentals (revenue/expense recognition, amortization schedules).

Progress toward or completion of relevant certifications (CFA, FRM, or CPA).

Experience with enterprise project tracking tools (JIRA, Confluence) and technical requirements gathering directly from business users.