At the end of last year I sent a State-of-the-Talent-Market email to colleagues. In that mail I wrote: @Ken Abbott, a frequent contributor to QuantNet, replied to my mail: Subsequently, he asked if I would elaborate on the job market in algo and HFT for this blog. The simple answer is yes, there are jobs in Algo/HFT, and some of them are paying very well. However, that jaw dropping salary that you heard from a friend is only going to the very best individuals with rarified talent. I have a large hedge fund client that is a pioneer in algo trading. I recently presented a candidate for a quant role at the firm, and the first thing the recruiter asked me about him was, “Does he have any medals?” “Medals?” I asked. “Yes, from math Olympiads.” As we talked further, it became clear that winning a medal at your country’s math Olympiad was okay, but really they’d prefer someone who had done well at the International Math Olympiad… Rarified indeed. As with most things, there’s a spectrum of jobs in this area. The above speaks to the jobs that are responsible for the high salaries and subsequent buzz around algo/HF trading. Here’s what I actually see in the market: Buy Side - Hedge Funds - Larger, well capitalized funds are looking for unique talent and may pay extremely well - Smaller funds want this talent too, but they can only pay by promising a reward based on returns. The majority of these funds struggle to make money, are very volatile, and the rewards tend to be marginal. I worked with an individual who worked at five funds over a period of ten years. I asked him to explain his work history, since hiring companies would need to understand why he moved around so much. His story, which I’ve seen numerous times, was Fund A failed, so I moved to Fund B, then B failed, so I moved to Fund C, which failed, etc. His earnings over the period weren’t any better (and probably were worse) than if he had taken a good quantitative developer job at an investment bank. What they look for when they hire - Best of the best talent. You do not need a Stanford or MIT degree, but you’ll need to impress a lot of people who interview you with your sheer intellect (a top school helps for entry level jobs, as these firms recruit heavily from top schools). An A level talent for Goldman Sachs may be a B+ player for a top hedge fund. These funds are relatively small and can afford to be selective. They usually hire opportunistically when they see the level of talent they want. Algo/HF - The funds that participate in algo/HF trading generally look for the following: PhD in a quantitative field Experience with high performance computing Excellent software development skills – the ability to turn quantitative analysis into systems Macro - Macro funds look for a very different profile. They use third party products for trade processing, risk, regulatory reporting, and other needs. The main challenges involve system integration and the ability to make adjustments on the fly to accommodate new trade types and new requirements. Typically these funds stress: Excellent software development skills (C# front to back is the norm) Excellent communication skills – nobody has time to explain things twice in a fast-paced trading environment Good instincts and the ability to work independently – you need to be able to understand how things are done at the firm, and do it w/o being managed Experience with a variety of financial products, trade booking, order management, and risk Sell Side - Banks With current regulations, banks can’t invest their own money in algo trading. However, they do employ algo/HFT quants and developers to conduct business on behalf of their clients and as market makers in fixed income markets. Equities Most algo dev/quant roles are on the equity side, as firms seek an execution advantage in equity markets which are now almost entirely electronic. Complex algorithms are deployed to assess market microstructure across a myriad of exchanges. I see roles in this area with some regularity. Generally these are dev/quant roles with an emphasis on excellent C++ skills and a strong background in a quantitative field. Fixed Income Fixed income markets have slowly moved to electronic exchanges over the course of the past two decades, but the migration has accelerated due to recent regulation that requires the majority of fixed income derivative contracts to be traded on exchanges. Algo roles in fixed income are concentrated on automating the process of making markets on electronic exchanges. For example, quoting a credit default swap involves a complex assessment of the market including analysis of the underlying equity where there is far more liquidity. Each fixed income instrument requires a different type of analysis. This is a new field, and trading desks are looking for outstanding individuals to research and implement strategies. These jobs pay well, but there aren’t a lot of them. What they look for when they hire Equities - Top notch developers with significant experience in high-performance computing C++ used almost exclusively R and KDB+ skills are often desired - Knowledge of equities market microstructure - Knowledge of machine learning and data mining - MS or PhD in a quantitative field Fixed Income - Top notch quantitative skills – generally a PhD in a quantitative field is required - Knowledge of machine learning and data mining - Knowledge of fixed income products – cash and derivatives - Software development skills Conclusion The above observations are generalizations. Every company has its own way of operating, and needs differ from firm to firm. And of course every individual offers a different blend of experience and abilities. If you’d like to discuss any of the above topics or determine if your background qualifies you for a specific role, I’d be happy to talk to you. You can reach me at firstname.lastname@example.org. LinkedIn profile: www.linkedin.com/in/peterwagner123 (I keep a listing of active quant roles here) Peter Wagner has a masters in computer science and spent 20 years developing trading and risk systems for major investment banks. He formed Affinity Resource Group in 2011 to apply his experience in the field to help firms find talented IT and quantitative professionals.