Nat Kilsby was right. The former head of operations engineering for Goldman Sachs turned COO of Quadrature Capital told us in March that hedge funds were all over Python coders, and that Python has become the language to learn for hedge fund jobs because it’s a bridge between research and technology. 

Eight months later, technologists say hedge funds’ demand for Python expertise is higher than ever. 

“As the use of machine learning techniques and statistical analysis becomes more influential in the investment process for funds, Python and associated libraries (Pandas etc) are replacing R, Java and C++,” says Dean Looney, a quant headhunter at London search firm Referment. Python simply offers quantitative technologist, “a lot more flexibility and functionality,” Looney adds.

Hedge funds don’t use Python for everything, but they use Python for a lot. Balyasny Asset Management, for example, is looking for data analysts conversant in Python to work on fundamental research, data gathering and processing, along with back-testing data-driven idea generation. However, it’s looking also looking for people who can code in C# to work on front office trading systems operating with sub-second latency. 

Python is too slow to replace C++, C# or Fortran on high-frequency systems, but for a lot of hedge funds and for a lot of the functions hedge funds require it for, this isn’t the point.  – “Python isn’t the fastest language on the world – but it’s fast enough for what hedge funds need it to do a lot of the time,” says Sean Hunter, a former Goldman Sachs technology VP and tech consultant. “A lot of hedge funds will have a Python notebook that they run once a day and that pulls in all their positions and performs all the risk calculations.”

Python also has the advantage of being easy to learn and use compared to C++ and Fortran, and it can be easily integrated with platforms like AWS as hedge funds move to the cloud. 

The upshot is what recruiters describe as a substantial increase in hedge funds’ demand for Python developers compared to anyone else. 

This is reflected in the job advertisements on eFinancialCareers. As the chart below shows, Python is cited in 39% of hedge fund technology job ads, compared to just 25% for C++.

Hedge funds like Man Group have long been exponents of Python, but until a few years ago many were still using R or Matlab. The popularity of Python packages like Pandas and Numpy which improve Python functionality have encouraged the shift. So, too, have things like Cython, which can make Python up to 30X faster. 

“Five years ago, it was C++ and Java, but Python is now king at hedge funds,” says another technology headhunter in the space. “As a language, it’s come an incredibly long way in recent years. – Python is a fully fledged object-oriented language, but is very easy to learn and to use. High-frequency funds will still use C++, but if you’re a mid-frequency fund, then Python is more than adequate.”

Looney says the ideal hedge fund hire now is a Python quant developer who rapidly translate quant traders’ ideas into actionable code. Good candidates can make £120k-£150k ($161k-$202k) in base salary in London, plus bonuses of 150% on top. 

Photo by Nick Fewings on Unsplash

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