Quantitative Developer

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Full time
Location: London
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Job offered by: London Stock Exchange
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Quantitative Developer Quantile offers market-leading optimisation services that reduce counterparty risk, notional and capital requirements to increase the efficiency and liquidity of derivatives markets, improve returns for clients, and make the financial system safer. We are part of LSEG’s Post Trade division, where we connect a network of participants and use advanced algorithms to reduce risk and release capital. Since launch, our services have eliminated trillions of dollars of gross notional through interest rate compression and billions of dollars in initial margin and capital requirements through counterparty risk optimisation. Our clients, including all top tier global banks, regional banks, buy-side firms and other large institutional market participants, are serviced from offices in London, New York and Amsterdam. The Strat team is responsible for designing, building and maintaining the code that handles the data priming, the model execution and the post-processing of the solution into a format that clients can consume. The biggest component of the role is writing and testing code, which is written in Python, so it is important to enjoy coding and be comfortable with designing and writing code in a large, shared codebase. Being comfortable with inter-library dependencies, Python package management and continuous development practices is also crucial. In addition to building the calculations, the Strat team is on the front-line when it comes to executing the multilateral optimization runs, which occur multiple times a week. This requires a high level of engagement with our Production team, to provide timely support during runs and help resolve issues as they arise in real time. A client-focused approach is therefore of paramount importance for the role. Successful candidates will build and support one or more of Quantile products. They work directly with our Production and Product Development teams to enhance the products based on feedback from clients and analysis of runs, as well as on strategic projects. Examples of relevant projects include: Implement Capital measures (e.g SA-CCR, or IMM) for FX, IR or Equity Enhance our Initial Margin optimisation to include cleared trades for multiple CCPs Implement a new service to move bilateral trades into clearing while maintaining risk and capital under control Combine risk capital products within a single multi-objective optimisation Improve the runtime performance by reducing the data set and solution search space Improve data flow, minimising manual steps, avoiding task duplication, and building an event-driven architecture Responsibilities: Develop enhancements to the model library to add new components and improve others. This will be a mix of strategic projects (3-6 months) and shorter-term tactical changes Become familiar with the data flow and the run processes and continually strive to improve them Investigate how to tune the model to create desired outcomes for clients Support live runs Essential: 2-5 years of experience building quantitative, data intensive products Excellent understanding of software development best practices (such as functional and OO paradigms and standard design patterns) and design principles (SOLID) Excellent understanding of commercial development practices such as testing, documentation, package management and SDLC Excellent understanding of Python for numerical programs. In particular, pandas and numpy are a must Excellent problem-solving skills Strong communication skills (the role will involve explaining complex algorithms to colleagues with varying technical and mathematical experience) Desirable: Knowledge of UNIX Understanding of linear and mixed integer programming, and convex optimisation Experience with at least one commercial or open-source optimisation library or a mathematical modelling language Understanding of financial derivatives, margin and counterparty credit risk measures A solid mathematical background (numerical methods, linear algebra, partial differential equations, probability & statistics) Knowledge of AWS This role is a hybrid working role, with a blended approach of home and office working. Quantile is an Equal Opportunity Employer.

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