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Chief Technologist/Junior Quant Trader, London (office not yet purchased) |
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Chief Technologist/Junior Quant Trader (this is an archived job displayed for information purposes only)
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Quality coder required to join new London trading operation of large established Swiss energy shop, in a key-worker role critical to the whole operation’s success, to build trading tools in greenfield environment side by side with head trader as part of the trading team. 10% quant(y), 30% data wrangler, 100% devel legend, with a large dash of common sense and wider perspective. UNDER OFFER-- This role is currently under offer. My client is a large established Swiss energy trader which has decided to create a significant London presence. They have hired a major-league head trader and asked him to create his own team. He promptly poached his (ex) right-hand man to create the core IT capability for the desk, but personal issues intervened (Australia beckons) and he now needs someone else. You’ll be a highly skilled developer with a maths-friendly-attitude and a focus on solving the whole human problem rather than tuning the nuts off the fun bits and ignoring the boring bits. Ideally you’ll have had exposure to the markets and trading, but this is less important than sheer common sense and drive. The traders will be bringing the market knowledge, you’ll be bringing yourself as the API to the computers/DBs. There is also scope for this job to evolve towards a quant.trading position. It’s Greenfield so you can choose your own languages and libraries. You like python? Go python. You like R? Go R. You like SDLC/Waterfall/spec.-signoffs? Go away. You’ll be banging together huge datasets, so OLAP skills are useful, or at least solid understanding of relational fundamentals vs time-series’ intra-table implicit relationship(s). Understanding how and why to setup optimization problems, to constrain them, to choose different optimizer approaches, is all pretty important, especially a sufficiently deep understanding/maths-appreciation to allow sane choices of alternate approximations more achievable under the problems’ conditions. Strong econometrics/statistics is also very useful, especially depth in non-linear or non-parametric techniques to cope with the real-world features of the energy markets. So you’re likely to have a very quantitative post-grad finance degree or a solidly maths-based under-grad degree such as physics or electrical engineering. Sample project: chat with the boss about a trade/strategy idea, find&wrangle the data to test it, test it [& it’s good], identify the best ongoing signals for using the strategy day-to-day, build something to calc these continuously, build a dumb GUI to present these analytics to the trader in usable format. May or may not involve the use of stickytape and string. This is expected to be a key-man position for the whole London operation, and they’ll pay bonus accordingly. Key Point is: can you work side-by-side with the traders to create the decision support and trading tools that will let a small tight well-capitalised trading shop create some serious PnL? |
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