Quantitative Developer – Python, Django

This is a fully remote position, open to applicants in Latin America.

📋 Description

• Develop and sustain production-grade Python computing for PRISM and associated risk metrics.

• Create and manage the reference-set harness to validate model or classification alterations in CI.

• Troubleshoot production scoring errors and differentiate between code, data, and methodology problems.

• Address underlying categories of bugs rather than just individual instances.

• Make determinations on straightforward classification inquiries and escalate complex cases involving structured products, buffered ETFs, and private assets.

• Assess the impact of changes and maintain a tested rollback for each model or classification modification prior to release.

• Ensure the scoring process remains efficient as the volume of portfolios and securities increases.

• Manage a live PRISM defect from start to finish within the first 90 days.

• Implement and connect a reference-set harness into CI, making it a mandatory check.

• Relieve the Principal Engineer of scoring incidents.

⛳️ Requirements

• Proven experience in production Python that you have deployed and maintained — not merely a prototype or notebook.

• Proficiency in Django — including models, migrations, tests, CI, and code reviews, meeting the same standards as any other engineering role.

• Expertise in SQL and data management at scale — utilizing pandas, numpy, and handling portfolio-sized datasets.

• Background in testing and validation engineering — integrating reference-set/golden-data harnesses into CI, beyond just unit tests.

• Familiarity with large-scale systems, data pipelines, or automated processes (such as trading systems, scrapers, or data adapters).

• Understanding of US market structure and asset classification — including equities, fixed income, funds, ETFs, annuities, structured products, cash equivalents, and private assets.

• Fundamentals of risk modeling and scoring — encompassing concepts like volatility, correlation, concentration, and tail measures.

• A solid work history with tenures of 18 months or more in previous positions.

• Practical experience with options, structured products, or derivatives is advantageous.

• Knowledge of tax-aware analytics (after-tax return, cost basis, loss harvesting) is beneficial.

• Focus on production software experience that encompasses development, deployment, and maintenance rather than primarily research-grade quantitative code, notebooks, or prototypes.

🏝️ Benefits

• Long-term opportunity to make an impact on production systems utilized in actual financial workflows.