This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Quantitative Developer based in the United States.
This role sits at the intersection of quantitative research and high-performance software engineering, focusing on the design and implementation of trading and risk systems used in fast-moving financial environments. You will translate complex mathematical models into production-grade software that powers pricing, execution, and risk analysis across financial instruments. The work spans low-latency system design, market data processing, and real-time analytics, with a strong emphasis on performance, correctness, and scalability. You will collaborate closely with quants, traders, and risk professionals to refine models and ensure systems behave reliably under real market conditions. The environment is highly technical and precision-driven, where engineering quality directly impacts trading decisions and financial outcomes. This is a hands-on role with significant ownership across the full lifecycle of quantitative systems.
Accountabilities:
- Design and implement low-latency trading, pricing, and risk systems using C++, Java, or Python.
- Translate quantitative models into production-grade implementations with a focus on accuracy and performance.
- Build and maintain market data ingestion, normalization, and processing pipelines for high-frequency data.
- Develop pricing engines for derivatives and structured products, ensuring rigorous validation against benchmarks.
- Implement risk, P&L attribution, scenario analysis, and stress-testing systems used for decision-making.
- Optimize critical-path systems through profiling, performance tuning, and concurrency improvements.
- Build backtesting and simulation frameworks for strategy evaluation using historical and synthetic data.
- Ensure systems are fully observable with robust logging, metrics, and audit trails.
- Support regulatory and compliance reporting with reproducible and auditable outputs.
- Participate in incident response for trading-critical systems and ensure rapid resolution of production issues.
- Maintain detailed technical documentation, including system design, architecture, and operational runbooks.
- Mentor junior engineers and contribute to strong engineering and quantitative culture.
Requirements:
- Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, or a related quantitative field.
- 6+ years of software engineering experience, ideally within fintech or trading environments.
- Strong programming skills in C++, Java, and/or Python (multi-language experience preferred).
- Solid understanding of financial markets, instruments, and quantitative modeling principles.
- Hands-on experience building low-latency, high-throughput distributed systems.
- Familiarity with market data systems and FIX protocol is highly desirable.
- Strong knowledge of risk systems, P&L attribution, and trading workflows.
- Experience with concurrency, high-performance computing, and systems optimization.
- Excellent debugging, profiling, and performance tuning capabilities.
- Strong communication skills and ability to collaborate with technical and business stakeholders.
- Exposure to derivatives pricing libraries (e.g., QuantLib) or kdb+/q is a plus.
- Advanced degree or specialization in a quantitative discipline is an advantage.
Benefits:
- Competitive annual salary ranging from $100,000 to $150,000 based on experience.
- 100% remote role within the continental United States.
- Full-time W2 employment with long-term, multi-year engagement stability.
- Comprehensive benefits package including healthcare and standard employee benefits.
- Opportunity to work on high-performance trading and risk systems in fintech.
- Exposure to advanced quantitative modeling and real-time financial infrastructure.
- Strong engineering culture focused on performance, precision, and innovation.
- Career growth opportunities in quantitative engineering and financial technology.