Quantitative C++ Developer


Trading and Risk solutions provider based in Montreal seeks Quantitative C++ Developers to join their Modeling and Quantitative Data team.As a C++ Quantitative Developer, you will discover, design, develop and test models to value positions and construct quantitative data (curves, volatility cubes, correlation matrices, etc.) or calculate market risk (VaR, greeks, etc.) in real-time across all asset classes including Crypto.

Our risk models are used by some of the largest, most prestigious financial institutions around the world, ranging from global investment banks to multi-strategy hedge funds.DutiesDesign and development of models for pricing positions and calculating market risk metrices for all asset classes (equity, credit, FX, fixed income, commodities, crypto, and their derivatives)Write modern, clean, reusable, well tested source code in C++ that scales and performs well across large distributed systems (based on our high-performance grid computing platform)Leverage Python, SQL and Snowflake to analyze the model inputs or construct model inputsCreate methodology documentation to support model validation when needed3-4 office days per week, based in Montreal.Total compensation (base & bonus) approximately $200K – $230K CADFor next steps, please kindly send me an updated resume to denisanalyticrecruiting.comRequirementsM.S. or PhD in mathematics, physical sciences, or engineering preferredExcellent quantitative and programming skills with 3-5 years’ experience in large-scale C++ development and program design as well as data intensive productsExperience with other programming languages (Python, Java) is an advantageUnderstanding of financial derivatives, market conventions and their implementation is a mustExperience working on yield curves (OIS, Libor, Cross-currency, etc.), inflation curve, volatility surfaces, interest rate volatility cubes (eventually live/intraday) as well as the data to build them is highly desirableExperience in developing risk management tools such as VaR, Monte Carlo, scenario analysis and P&L is preferred



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