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| Job Location | London |
| Education | Not Mentioned |
| Salary | Competitive salary |
| Industry | Not Mentioned |
| Functional Area | Not Mentioned |
| Job Type | Permanent,full-timeB |
Interest Rates Systematic Market Making Strat - Assoc/VP level London based In this role our client look to their Engineers to own the business, rather than support it. As a systematic trading group, they aim to leverage best-in-class technology and quantitativeapproaches to produce scalable and repeatable returns across the assets they trade, as well as innovation in how the division provides liquidity to the client franchise. They are looking for a Quantitative Engineer with a passion for using technology to drivecommercial results, to focus on building the electronic Rates business. The team structure is designed to embrace hybrid skillsets across software development, quantitative research and trading. The group is a global cross-asset systematic market making businesscovering FX, Commodities, Interest Rates, and Credit. As an automated trading business, they manage both the financial and operational risks of this business. They focus on providing liquidity to clients, primarily via electronic channels, in Bonds, Swaps,Futures and ETFs. Their mission is to grow the franchise, increase innovation across the division, generate standalone revenues and run the business in a truly systematic fashion such that required human involvement/intervention scales sub-linearly with thenumber/volume of products they trade or clients they serve. Responsibilities: Development of automated quoting, risk-management and hedging algorithms for the electronic Rates franchise in EMEA, working as part of a global team. Quantitative analysis of inquirydata and market tick-data to optimize the quoting and hedging systems. Generate and research ideas for system enhancements that drive commercial performance. Working with sales and technology teams and constantly iterating to ensure connectivity and accessto liquidity evolves with the market. Understand the regulatory and supervisory environment and demonstrate ownership of their obligations and responsibilities under this. Requirements: Strong academic background in Computer Science or an analytical fieldsuch as Mathematics, Physics, Engineering, Economics etc. Strong software engineering background. Ability to analyze large data sets and draw commercial conclusions. History of productive interaction with other groups, especially sales, trading and other technologyteams. Experience building Java-based systems in a Linux environment, with strict requirements for low-latency (microseconds count) and deterministic performance. Relevant markets/securities/trading experience is a plus but not required. Experience with Pythonfor big-data analysis. Low-latency messaging, network protocols, network I/O in Java, JNI.