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Interest Rates Systematic Market Making Strat - Assoc/VP level
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 quantitative approaches 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 drive commercial 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 business covering 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 the number/volume of products they trade or clients they serve.
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 inquiry data 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 access to liquidity evolves with the market.
Understand the regulatory and supervisory environment and demonstrate ownership of their obligations and responsibilities under this.
Strong academic background in Computer Science or an analytical field such 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 technology teams.
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 Python for big-data analysis.
Low-latency messaging, network protocols, network I/O in Java, JNI.