Full Stack Quantitative Developer

Our client, an investment firm, is seeking a Full Stack Quantitative Developer to join their team in Los Angeles, CA, Dallas, TX, or New York, NY!

Responsibilities

• Build full-stack applications across the credit, private credit, and structured products platforms — backend services, APIs, data pipelines, and modern web front ends used by various business teams across the firm.
• Develop quantitative models and analytics for fixed‑income and structured product valuation, cash flow projections, scenario analysis, and portfolio risk decomposition.
• Integrate third‑party systems including Geneva (portfolio accounting), market data vendors, CRM platforms, and administrative platforms, design clean, well‑tested adapters and reconciliation logic.
• Participate in the migration of legacy .NET/C# applications and SSRS reports to modern, scalable architectures (TypeScript/React front ends, Python or .NET services, cloud‑deployed) with responsive UX across desktop and mobile.
• Own data quality end‑to‑end — ingestion, normalization, validation, and lineage — for firm‑wide positions, partnering with the data management team on governance and controls.
• Build reporting and BI spanning Tableau dashboards, internal web tooling, investor reporting, and ad‑hoc requests for portfolio composition and DDQ responses.
• Translate business needs into engineering — gather requirements directly from PMs, analysts, risk, IR, and operations; document functional and technical specs; write clear UAT plans and lead testing.
• Ship like an engineer — write tests, use source control (GIT/TFS), open clean PRs, manage tickets in DevOps, deploy through CI/CD, and monitor what you ship in production.
• Use AI coding assistants well — accelerate delivery, reduce boilerplate, and improve code quality, while applying the verification, security, and review standards described later.

Required Qualifications

• Bachelor's degree (or higher) from a top‑tier university in computer science, mathematics, physics, financial engineering, or another quantitative discipline.
• 5+ years of professional software engineering experience, including production ownership of customer‑facing or business‑critical systems.
• 2+ years working in capital markets, ideally at a hedge fund, asset manager, investment bank, or financial technology vendor — with direct exposure to fixed income, structured products, derivatives, private credit, or CLOs.
• Demonstrated success delivering full‑stack applications end‑to‑end, from requirements through production deployment and support.
• Solid understanding of fixed‑income securities, bank loans, and credit instruments.
• Familiarity with private credit deal lifecycle: sourcing, underwriting, closing, ongoing monitoring, amendments, and valuation.
• Awareness of portfolio accounting concepts (Geneva exposure is a plus) and portfolio risk frameworks (Bloomberg Port, RiskMetrics or equivalent).

Preferred Qualifications

• Prior experience at a credit‑focused hedge fund or alternative asset manager.
• Exposure to Advent Geneva or comparable portfolio accounting systems.
• Experience building data lakes / lakehouses and modern ELT pipelines (Snowflake, Databricks).
• Open‑source contributions or published quant / engineering writing.

Technical Skills - Core

• Backend: REST APIs, asynchronous services, and microservice patterns. Python or NET/C# experience strongly preferred given existing systems.
• Data: expert SQL (window functions, query tuning, set‑based thinking); experience with NoSQL/document stores.
• Quant / numerical: comfortable with NumPy/pandas (or equivalent), basic statistics, fixed‑income math (duration, convexity, OAS), and cash flow modeling.
• Tooling: Git (or TFS), CI/CD, DevOps, Confluence, unit and integration testing frameworks.
• Cloud: experience deploying and operating services on Azure or AWS is a plus.

General Skills

• Strong analytical and practical problem‑solving skills; you reason from first principles and verify assumptions.
• Excellent written and verbal communication; able to explain technical work to PMs and senior executives.
• Self‑starter with strong work ethic; comfortable juggling multiple workstreams under deadline pressure.
• Detail‑oriented, with high standards for code quality, data accuracy, and operational discipline.
• Team player who collaborates well across technical and non‑technical groups.