Quantitative Developer (Fintech)

Requirements

• 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.

Benefits

• Competitive base salary commensurate with experience, plus benefits.