Quantitative Analyst - Credit Derivatives

Hudson River Trading (HRT) is hiring a Quantitative Analyst to support the buildout of our ambitious efforts to develop and deploy global credit derivatives strategies. In this role, you will develop and apply stochastic models and other techniques, such as data analysis or statistical/probabilistic machine learning, to guide and support systematic trading strategies.

You will be joining our Macro Analytics team, which sits within the broader Algorithmic Development group at HRT. You will contribute to the development and organizational deployment of HRT’s central analytics infrastructure to support alpha generation, PNL monitoring and decomposition, and risk management. You will collaborate with other researchers and teams across the firm to optimize existing tools and models, with varied opportunities to contribute novel ideas in a meritocratic environment.

Interest and experience in programming are essential in this role because you will be responsible for not only research and prototyping, but also writing production code. Expert C++ is a requirement, and familiarity with scientific Python is a plus.

Responsibilities

• Development and improvement of best-practice pricing/risk infrastructure and toolset for corporate bonds, CDS, and other linear credit derivatives.
• Development of cutting-edge pricing/risk stochastic models for callable bonds and other nonlinear credit/hybrid derivatives.
• Monitoring and analysis of market data, including the generation of derived data and development of appropriate pipelines to feed data into models to produce alpha signals.
• In collaboration with appropriate teams, deployment of all the above and application to systematic trading strategies and risk management.
• Research beyond best practices: alpha generation process and machinery, statistical and machine learning, stochastic modeling, algorithms, numerical and computational implementation, design patterns, etc.
• Promotion of derivatives culture within HRT.

Profile

• Advanced degree (Masters, PhD or equivalent) in mathematical or computational finance, or in a quantitative discipline (mathematics, statistics, physics, computer science, engineering), with exceptional academic credentials.
• Professional experience with credit derivatives modeling, research and development, and support of trading businesses. Working knowledge of credit derivatives instruments, pricing and risk models, and numerical/computational implementation.
• Strong professional C++ skills required. Experience working with data in Python (including NumPy, pandas, scikit-learn, etc.) is a plus.
• Attentive to detail, striving to achieve deep understanding and top-of-class implementation.
• Strong communication skills with the ability to explain complex models to a less familiar audience.
• Outstanding work ethic and capacity to thrive in an ambitious, fast-paced environment.
• Entrepreneurial mindset and ability to connect the dots between mathematical models and real-world market behavior.

Annual base salary range of $175,000 to $250,000. Pay (base and bonus) may vary depending on job-related skills and experience. A sign-on and discretionary performance bonus may be provided as part of the total compensation package, in addition to company-paid medical and/or other benefits.