Quantitative Engineer – Risk Analytics

swiss

Quant Group provides quantitative services, consultancy, and products for financial and industrial clients, including a number of global Fortune 500 companies. Our business edge originates from the effective translation of Intelligent Technology into measurable, bottom-line client value. swiss

Quant Group is a privately held company incorporated in 2005 as a spin-off of ETH Zürich.

You will join a cross-functional team of quant engineers and quant developers building and operating a state-of-the-art, cloud-based portfolio risk system used by leading financial institutions.

The team covers the entire development and production cycle — risk model development, implementation, testing and monitoring — with strong role interchangeability amongst team members. In a highly innovative and collaborative environment, you will help create the next generation of financial risk models and bring them to life as software components and services.

Our multi-asset class risk engine covers a large set of risk factors, instrument types, and portfolio risk analytics. Ongoing efforts focus on expanding coverage, improving accuracy and performance, and on building AI-assisted and agentic capabilities into both our products and our own engineering workflow.

You will also have the opportunity to collaborate with our Capital Market Technologies team and gain exposure to client-facing quantitative projects, particularly risk models for Central Counter parties (CCPs), including margin methodologies, stress testing, backtesting and model validation.

• Design, build and deliver robust, production-quality models and code within a unified library
• Implement, test and monitor risk analytics across the full development and production cycle
• Contribute to the expansion of instrument, risk-factor and analytics coverage of the risk engine
• Enhance the usability of our portfolio risk, performance analytics and portfolio construction tools
• Take a quantitative idea from proof-of-concept through to client deliverable
• Use modern AI coding assistants and agentic tooling to accelerate development, testing and documentation, while owning the correctness and quality of the result
• Contribute to client-facing capital markets projects, including model development, validation and review in line with regulatory standards (e.g. EMIR, CPMI-IOSCO PFMI, Basel/FRTB, Solvency II)
• Deliver high-quality documentation, validation reports and presentations to clients and senior stakeholders
• Communicate and explain model results and modelling assumptions to stakeholders with diverse levels of domain knowledge

• Higher university degree in a quantitative discipline such as Quantitative Finance, Mathematics, Physics, Computer Science or Engineering (PhD a plus)
• Solid experience in quantitative model development, testing and documentation
• Good understanding of major financial markets and products. Knowledge of factor models, asset allocation and derivatives valuation models is a big plus
• Exposure to practical portfolio management or risk management is beneficial
• Good understanding of statistical and econometric modelling techniques, e.g. time series analysis, regression models and machine learning
• At least 3 years of Python coding experience; other languages are a plus
• Knowledge of data stores (SQL and/or No
  
  SQL) is required. Exposure to CI/CD technologies (Google Cloud, Jenkins, Docker, Kubernetes) is beneficial
• Hands-on experience with AI coding tools (e.g. Claude Code, Codex, Gemini CLI, Cursor, Windsurf) and a thoughtful, critical approach to integrating them into a professional engineering workflow
• Familiarity with agentic application development — LLM-based agents, tool/function calling, retrieval-augmented generation (RAG), and the Model…