Quant Developer (FinTech)

Job Summary

We are seeking an experienced Quant Developer (FinTech) to build low-latency, high-reliability trading, risk, and analytics systems for fintech applications. In this role you will partner closely with quants and traders to translate mathematical models into production-quality software that meets strict performance, accuracy, and operational requirements.

Key Responsibilities

• Design and implement low-latency trading, pricing, and risk systems in C++, Java, or Python.
• Translate quantitative models from prototypes (often in Python or MATLAB) into production-quality implementations.
• Build robust market data ingestion and normalization pipelines for high-volume tick data.
• Develop pricing libraries for derivatives and structured products, with rigorous testing against analytical benchmarks.
• Implement risk engines, P&L attribution systems, scenario analysis tools, and stress-testing capabilities used by traders, risk managers, and quants to make informed decisions under uncertain market conditions.
• Profile and optimize critical-path code for latency and throughput, applying systematic measurement, targeted improvements, and data-driven validation to deliver quantifiable gains in throughput, latency, or resource efficiency.
• Build comprehensive backtesting and simulation infrastructure that lets researchers evaluate strategies against historical data and synthetic scenarios with reproducible, audit-friendly results.
• Collaborate closely with quants, traders, and risk officers to refine models and tooling.
• Implement regulatory and compliance reporting workflows where applicable, ensuring outputs meet jurisdictional requirements, are auditable end-to-end, and can be reproduced reliably for retrospective analysis.
• Ensure full observability of trading systems with appropriate logging, metrics, and audit trails.
• Lead incident response for trading-critical issues with calm and rigor.
• Maintain comprehensive, current technical documentation — including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures — so that the system remains supportable, auditable, and easy to onboard new engineers onto over time.
• Mentor junior engineers and contribute to engineering culture in the team.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, or a related quantitative discipline.
• Six or more years of software engineering experience, with significant time in fintech.
• Strong programming skills in C++, Java, or Python (preferably more than one).
• Solid grounding in financial markets, instruments, and basic quantitative methods.
• Hands-on experience building low-latency, high-throughput systems.
• Experience with market data systems and FIX protocol implementations.
• Strong understanding of risk and P&L attribution.
• Experience with high-performance computing patterns and concurrency.
• Excellent debugging, profiling, and performance-tuning skills.
• Strong communication and documentation skills.
• Experience with derivatives pricing libraries (QuantLib).
• Familiarity with kdb+/q or similar columnar tick databases.
• Exposure to GPU-accelerated pricing or risk computation.
• Experience with cloud-native fintech architectures.
• Advanced degree in a quantitative discipline.