The quantitative risk management function within financial risk management is responsible for the development of the Firm’s methodologies for setting margin requirements and analyzing other risk issues. The Senior Quantitative Model Engineer will work closely with the other quantitative risk management team members, business users and IT colleagues to implement and test models for pricing and risk management of complex financial derivatives, as well as to support and enhance existing systems and QRM tools in that domain.
Primary Duties and Responsibilities:
To perform this job successfully, an individual must be able to perform each primary duty satisfactorily.
- Design quantitative libraries, test automation tools and frameworks using best industry practices and innovations, and enforcing rigorous and consistent standards
- Implement and test QRM’s models based on the model specification, working closely with others on the team and outside of the department.
- Develop and validate high-performance numerical algorithms, conforming to high reliability and accuracy standards of the organization.
- Write and review documentation for the QRM Library API, User Manuals, and Test Plans.
- Implement standards, processes, and tools for numerical library testing and code quality controls.
- Review implementation of complex models and algorithms focusing on requirement. verification and code quality. Conduct code review with peers, model validators and model developers.
- Provide production support for the numerical libraries and risk management systems.
- Provide integration support to the application consuming QRM libraries.
- Provide support to business users explaining the numerical output and investigating issues.
The requirements listed are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the primary functions.
- Software and Programming:
- Extensive programming background is required, with an emphasis on numerical algorithms and scientific computing.
- Demonstrated experience developing and maintaining enterprise level software. Proven record of delivering major functionality in a collaborative software development setting.
- Mathematics and Quantitative Finance exposure with a demonstrates understanding in (at least) three of the following technical areas:
- Pricing and volatility modeling
- Linear Algebra
- Monte Carlo simulation
- Numerical methods and optimization
- Risk Measures and Margin Models (e.g. VaR, expected shortfall; SPAN, TIMs)
- Statistical analysis
- Probability Theory and Stochastic processes
- Univariate and multivariate statistics and econometrics (e.g. time series analysis, fat-tailed distributions, copula, etc.)
- Portfolio theory
- Strong problem-solving skills. Be able to accurately identify a problem's source, severity, and impact to determine possible solutions and needed resources.
- Ability to challenge model methodologies, model assumptions, and validation approach.
- Strong financial products knowledge and familiarity with markets, basic trading and hedging strategies, especially for equity derivative products.
- Good interpersonal, verbal and written communication skills. Able to explain highly technical information to different audiences with varying levels of technical expertise.
- Able to follow sophisticated theoretical model documentation as well as create research notes and technical documentation according to OCC/QRM’s model documentation standards. Able to explain complex and technical information in a clear and concise manner. Must demonstrate proven technical writing skills.
- A good team player.
- Expert level proficiency in Java or another object-oriented language.
- Experience with numerical libraries and/or scientific computing.
- Experience with automated Quality Assurance frameworks for unit, system, and performance testing.
- Experience in (at least) one scripting language such as Python, R or MATLAB.
- SQL is required, non-relational DB and other Big Data experience preferred.
- Experience with code repositories, build and deployment tools (e.g. Git, GitHub, Jenkins, SVN).
- Experience in Agile/SCRUM framework is desired.
- Graduate degree in a quantitative/computational field such as statistics, financial mathematics, quantitative finance, computer science, physics, mathematics.
- 7+ years of relevant experience