Full Stack Quantitative Developer - Capital Markets-Hybrid in NYC / Dallas / Los Angeles-Direct Client Opportunity-Only Locals

Job Title: Full Stack Quantitative Developer - Capital Markets
Location: Remote
Hire Mode: Contract To Hire
Primary Skills: Quant Models, Capital markets, Investment Banking, Hedge Funds.

Job Description

Requirements

Education

Bachelor's degree (or higher) from a top-tier university in computer science, mathematics, physics, financial engineering, or another quantitative discipline.

Experience

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.

Technical Skills Core

Languages: strong proficiency in at least one of Python, C#/.NET, or TypeScript/JavaScript, and working competence in a second

Backend: REST APIs, asynchronous services, and microservice patterns. Python or NET/C# experience strongly preferred given existing systems

Frontend: modern JavaScript frameworks (React/Angular), responsive web design, HTML5/CSS, and cross-platform optimization for mobile

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

Reporting / BI: Tableau dashboard development or SSRS a plus.

Domain Knowledge

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).

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

Key Responsibilities:

Build full-stack applications across our 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 firmwide 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 in this document

Approximate Time Allocation

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This is a hands-on builder role. A reasonable target distribution:

60% development - services, APIs, front-end, quant models, data pipelines

20% reporting and analytics development - Tableau, SQL, internal dashboards, investor / DDQ outputs

10% requirements gathering and analysis - partnering with the business

10% production support, code review, and mentoring.