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5 specialist programming languages to stand out in finance

Chances are if you want an engineering job in finance, you'll be working with one of the major programming languages: C++. Java. Python and so on. As your role becomes more specialized, however, knowledge of alternate languages becomes more desirable. Here are specialist programming languages and the situations in which they stand out above their more generic counterparts.

R for Data Science and AI

Starting off with a language that's very well respected yet almost criminally unused in finance, R is regarded as one of, if not the best language for artificial intelligence as it is geared towards mathematicians. SitePoint identifies key features of the language as linear and nonlinear modeling, time series analysis, classification and clustering. Richard Hickling, founder of crypto trading and research company ProfitView, says it's "so useful for AI"

R receives a lot of love in the FAANG space. Amazon, Google and Meta are the three primary R users in that space.

So why hasn't finance taken to it? Despite top quants like ex-Citadel analyst Jeffrey Ryan singing its praises, Python is preferred in banks because their focus is computer science over data science. Python is also much better for trading systems than R, which has some typing issues that affect its speed of performance.

So is R worth learning? Certainly, if you don't see finance as the be all and end all. It may not be widely used, but it will round out your repertoire as a data scientist and gain the affection of Rs proponents while also opening you up to a possible move into FAANG. According to the Stack Overflow survey, less than 5% of engineers use it, making it a rare sight as well.

KDB+ for Databases

KDB as a language has waned in popularity amongst developers as the years have progressed, but the demand for it from employers is stronger than ever. The pay you can earn from it is also very attractive: KDB development jobs have been known to pay up to $600k in New York.

So what makes KDB so attractive? It can process large amounts of high frequency data effectively, making it perfect for algorithmic trading systems. 

While using R was a case of either/or with Python, KDB can instead be used alongside it to streamline the process. Saeed Amen, co-founder of Turnleaf Analytics calls it "the heavy duty workhorse," behind low latency python code.

VHDL for High Frequency Trading

In HFT, every picosecond counts. Different trading firms try a variety of methods to speed up their algorithms. Hickling says that"for big number crunching and HFT, they use GPUS;" one of the top languages for getting the most from that hardware is VHDL.

Instead of processing graphics for video games, these GPUs (or in some cases FPGAs) act as accelerators and coprocessors which, according to trading firm Maven Securities speeds up "data analysis and processing in research and production environments."

VHDL seems like the perfect language to learn for engineers with a passion for physical components. If VHDL itself doesn't tickle your fancy, another language identified by Hickling is Verilog.

Lua for Scripting

If you like gaining a better understanding of how the broader languages handle scripting, learning Lua is a worthwhile pursuit; Hickling says it's "typically embedded within other languages" but says that using it by itself makes it "cleaner and more succinct."

Lua isn't widely used in a professional setting according to Stack Overflow, with just over 3% of respondents to their survey saying they use it on a professional basis. Those that do use it earn a decent wage though; the survey says Lua coders have an average wage of $79.6k, higher than Java C++ and Python

There might be a reason most engineers aren't learning Lua. Of the nearly 2800 respondents that coded in Lua, 57% dreaded using it. One engineer on Reddit commented that: "you will be missing out on tons of prebuilt modules by using Lua as opposed to Python or Node."

Solidity for Blockchain Engineering

Coinbase CEO Brian Armstrong says that even as confidence in crypto wanes, the best young engineers still want to be a part of it. If you're one such engineer, learning Solidity could be the thing to help you stand out.

Solidity is an object-oriented programming language built on the Ethereum blockchain. Developers using it have found themselves placed at crypto market makers, decentralized exchanges and hedge funds.

In yesteryear, the language was the next big thing, attracting sumptuous pay packages of up to $500k fresh out of college. Salaries have most certainly taken a hit in that department, but CEO of blockchain fintech zk-SPARK says demand for these developers is still high.

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Photo by Kenny Eliason on Unsplash

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AUTHORAlex McMurray Editor

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