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The 24-year-old AI quants on $350k might be making a big mistake

Quantitative researchers leveraging AI are hot property in financial services, with top firms capable of forking out up to $430k for fresh graduates. There are lots of pitfalls, however, both when preparing for a job and for picking one.  

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Speaking on a panel for the CFA Institute, Joseph Simonian, founder of AI quant consultancy Autonomous Investment Technologies, said coming into finance with no prior knowledge can be costly. Simonian's advice is to learn finance and economics first, and then to enhance your data science and machine learning techniques after that.  

Knowledge of some sectors may help more than others. Simonian said he "always get[s] excited" when he sees AI research on commodities. Commodities research "is typically of high quality," he added. Involving yourself in commodities research projects might give you the edge you need.

It also helps to be choosy about where you apply. Simonian says that joining a newer or smaller firm will give you "a little bit of an advantage," as they have the "luxury of starting from the ground up." Billion dollar funds may end up culling some of their early experiments with AI by comparison. 

Big firms may also be risk-averse. Simonian says institutions like banks have a "very strong need to explain their products to their client," and will opt for transparent algorithms with comparatively underwhelming performance. At the smaller trading firms, this kind of oversight is often overlooked in favor of results.

It's not all about finance knowledge, though. If you have the requisite skillset. Millennium's Miami technology head said recently that it's much easier to train someone with no finance fundamentals than someone with no mathematics fundamentals. On the other hand, presumably it's even easier to not have to train someone in either.

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AUTHORAlex McMurray Editor

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