Quantitative Developer

As a Quantitative Developer for Risk Platform Infrastructure, your role will involve architecting and overseeing the development of highly reliable and scalable risk infrastructure to support front-office decision-making across various asset classes such as equities, commodities, fixed income, and FX. You will be responsible for building robust systems that deliver accurate pricing, risk assessment, and analytics within production constraints. **Key Responsibilities:** - Own the architecture, design, and delivery of the quant infrastructure supporting front-office risk and analytics. - Develop scalable frameworks for valuation, risk assessment, scenario analysis, and lifecycle modeling across multiple asset classes. - Ensure platform reliability through robust end-of-day (EOD) processing pipelines, model calibration workflows, and automated regression testing. - Implement standards for versioning, model governance, and platform health monitoring to maintain system integrity over time. - Design flexible infrastructure to accommodate client-specific configurations without compromising performance or maintainability. - Collaborate with engineering and product teams to align platform design with business and technical requirements. **Qualifications Required:** - 3-5 years of experience in quantitative development or financial engineering with exposure to various asset classes. - Strong engineering mindset with a focus on system reliability, maintainability, and performance. - Proficiency in Python and familiarity with modern software development practices such as CI/CD, testing, and observability. - Experience in building and operating quantitative infrastructure in production environments, particularly for pricing and risk analytics. - Demonstrated ability to lead and develop technical teams. - Sound understanding of trade lifecycle modeling, model calibration, and data orchestration within a risk platform context. In addition to the above, it is essential that you have a track record of delivering and operating robust quantitative systems at scale in a front-office or risk platform environment. Your experience in designing systems for automated recovery, failover, and monitoring of analytics jobs will be advantageous. Familiarity with distributed computing, EOD risk workflows, and large-scale job orchestration tools like Airflow and Prefect will also be beneficial. Previous experience in integrating complex model libraries into production platforms while ensuring reliability and transparency will further enhance your profile.,