Senior Software Engineer

Our client is seeking a Senior Software Engineer to join its esteemed Quantitative Risk Management division in Chicago, Illinois.

Key Responsibilities:
In the capacity of Senior Software Engineer in Quantitative Risk Management based in Chicago, you will assume a pivotal function in fortifying the future security of global financial markets through the development of sophisticated risk models deployed across international exchanges. Your daily undertakings will involve close collaboration with quantitative analysts, business stakeholders, technology professionals, and validation teams to introduce new models or refine existing frameworks. You will be entrusted with designing robust prototypes alongside automated testing architectures that underpin the dependability of essential risk management systems. By engaging in code reviews and presenting analytical findings to diverse audiences within the organization, you will help sustain rigorous technical standards. Your remit extends beyond programming as you provide indispensable support during model releases, resolve integration challenges with production applications, and facilitate the introduction of novel financial products. Success in this role is predicated not only upon technical acumen but also upon refined communication skills and an unwavering commitment to collegiality within a highly regulated context.

• Contribute to the formulation of advanced quantitative models for pricing, risk management, and stress testing of intricate financial instruments and derivatives.
• Scrutinize comprehensive model documentation, such as whitepapers and implementation notes, to ensure precision and adherence to prevailing industry standards.
• Design, implement, and maintain resilient model prototypes and testing utilities by employing best practices in contemporary software engineering.
• Undertake thorough quality assurance assessments on model implementations by devising test cases, automating unit tests, and constructing reference models as required.
• Present detailed test plans and outcomes to peers, model validators, and developers whilst integrating constructive feedback for perpetual enhancement.
• Participate diligently in code reviews for libraries, prototypes, and development tools to uphold exemplary coding standards throughout the team.
• Assist with model release testing, including margin impact analysis, as well as providing foundational support during integration with production applications.
• Aid in the development and evaluation of Model Development Tools encompassing databases, ETLs, service orchestration mechanisms, and CI/CD pipelines for streamlined workflow automation.
• Support large-scale backtesting of models utilizing historical data by configuring systems, executing tests, and analyzing results for veracity.
• Provide integration support for applications reliant upon quantitative risk management libraries whilst offering troubleshooting assistance during product launches.

Key Requirements:
To excel as a Senior Software Engineer in Quantitative Risk Management, you will bring substantial experience from quantitative finance or related fields, where you have implemented complex models into production environments. Your proven track record includes applying advanced mathematical concepts-ranging from stochastic calculus to machine learning-to solve real-world problems in risk management. You are adept at translating theoretical research into reliable software solutions using Python or similar languages while ensuring rigorous quality assurance through automated testing frameworks. Your ability to communicate clearly enables you to bridge gaps between technical teams and business stakeholders effectively. A collaborative spirit drives your interactions with colleagues across multiple disciplines as you contribute insights during code reviews or model validations. Familiarity with modern software development practices-including Agile methodologies-and experience integrating large-scale data systems further distinguish your profile. Above all else, your commitment to accuracy, responsibility, teamwork, and ongoing professional growth ensures that you consistently deliver high-quality outcomes aligned with organizational goals.

• Demonstrated mastery in quantitative disciplines such as financial mathematics (including derivatives pricing models), stochastic calculus, statistics, probability theory, advanced linear algebra, econometrics (time series analysis), machine learning methodologies (such as GARCH or copula), numerical methods (Monte Carlo simulation), optimization techniques, value-at-risk computations, expected shortfall analysis, stress testing protocols, backtesting procedures, scenario analysis approaches.
• Comprehensive understanding of markets and financial derivatives spanning equities, interest rates, and commodity products acquired through practical experience or academic study.
• Exceptional aptitude for resolving complex issues within multifaceted systems by judiciously identifying sources of concern and determining effective resolutions using available resources.
• Proficiency in producing technical documentation such as white papers or user guides tailored for both technical experts and non-technical stakeholders alike.
• Excellent interpersonal skills complemented by articulate verbal and written communication abilities that enable you to elucidate intricate concepts to colleagues at all levels of technical proficiency.
• A responsible approach to business operations combined with a dependable team-oriented mindset that fosters collaboration across departments.
• Capacity to constructively challenge established model methodologies or assumptions when appropriate whilst contributing positively to validation processes (desired).
• Experience architecting distributed data systems capable of scaling efficiently within enterprise environments (desired).
• Familiarity with Agile or SCRUM frameworks for managing software development projects effectively (desired).
• Advanced proficiency in Python programming for prototyping models or automating test processes together with experience utilizing scientific computing libraries; familiarity with automated quality assurance frameworks such as Junit or Pytest; solid grounding in relational database technologies including SQL; practical knowledge of office productivity tools like PowerPoint or Excel; exposure to additional languages such as Java or C++ is advantageous; understanding of object-oriented design patterns; experience with version control systems like Git; background in web service/API development; comfort working with non-relational databases or cloud-based platforms is beneficial.

What sets this company apart:

• This institution distinguishes itself as a linchpin of global financial stability.