Principal Quantitative Risk Python Software Engineer

***We are unable to sponsor for this permanent full-time role**

***Position is bonus eligible***

Prestigious Financial Company is currently seeking a Principal Quantitative Risk Software Engineer with strong Python experience. Candidate will collaborate with other Quantitative Risk Management (QRM) analysts, business users, data & technology staff, and model validation colleagues to implement new models and enhance existing models.

Responsibilities:

Support the development of quantitative models for pricing, risk management, and stress testing of financial products and derivatives.

Review model documentation including whitepapers and implementation notes.

Design, implement, and maintain model prototypes and model testing tools using best industry practices and innovations.

Review and conduct comprehensive quality assurance testing on the implementation of models and algorithms for both QRM Library and prototypes focusing on requirement verification, coding, and testing quality, which involves the constructions of test cases, automation of model unit testing and creations of reference models if needed.

Present test plans and test results to, and obtain feedback from peers, model validators, and model developers.

Participate in code reviews for QRM Library, model prototypes, and Model Development Tool.

Contribute to the model release testing including margin impact analysis and baseline support and troubleshooting during model library integration with production applications.

Contribute to the development and testing of Model Development Tool including databases, ETLs, services, orchestration, and CI/CD pipelines.

Support large-scale model back-testing using historical data, including system configuration, execution and analysis of results.

Provide integration support to the application consuming QRM libraries.

Support the launch of new products.

Provide quantitative analysis and support to risk managers on pricing, margin, and risk calculations.

Provide production support for numerical libraries and risk management systems as assigned per the QRM s support schedule.

Qualifications:

[Required] Strong quantitative skills, ability to demonstrate deep understanding in the following technical areas:

Financial mathematics (derivatives pricing models, stochastic calculus, statistics and probability theory, advanced linear algebra)

Econometrics, data analysis (e.g., time series analysis, GARCH, fat-tailed distributions, copula, etc.) and machine learning techniques

Numerical methods and optimization; Monte Carlo simulation and finite difference techniques

Risk management methods (value-at-risk, expected shortfall, stress testing, back-testing, scenario analysis)

[Required] Good understanding of markets and financial derivatives in equities, interest rates, and commodity products.

[Required] Strong problem-solving skills: Be able to accurately identify a problem's source, severity, and impact to determine possible solutions and needed resources.

[Required] Proficiency in technical and scientific documentation (e.g., white papers, user guides, etc.).

[Required] Good interpersonal, verbal and written communication skills. Able to explain highly technical information to different audiences with varying levels of technical expertise.

[Required] Business-oriented, responsible, and a good team player.

[Desired] Ability to challenge model methodologies, model assumptions, and validation approach.

[Desired] Experience in building distributed data systems.

[Desired] Experience in Agile/SCRUM framework.

Technical Skills:

[Required] Proficiency in Python for prototyping and test automation.

[Required] Experience with numerical libraries and/or scientific computing.

[Required] Experience with automated quality assurance frameworks (e.g., Junit, TestNG, Pytest, etc.) for model testing.

[Required] Experience in relational database technology and SQL query language.

[Required] Experience in office technology such as PowerPoint, Word, and Excel.

[Desired] Experience with other programming and scripting languages like Java, C , R, and shell.

[Desired] Effective application of data structure, design patterns, expertise in object-oriented design.

[Desired] Experience with code repository, build and deployment tools (e.g., Git, GitHub, Jenkins).

[Desired] Experience with development and testing of web services and API.

[Desired] Proficiency in non-relational DB and other Big Data, cloud-based experience.

Education and/or Experience:

Master s degree or equivalent is required in a quantitative field such as computer science, mathematics, physics, finance/financial engineering.

6 years of experience in quantitative areas in finance and/or development experience in model implementation and testing.

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