coding languages
Bank technology jobs: which coding languages to master and which to avoid
Coding languages |
Python is a language that always encourage people to learn.
Although Python is currently the most utilized programming language in finance, it may not be as fast as certain other languages. We employ it for data analytics as well as data analysis, research, and querying. Python is the language of AI and machine learning as well, and both are becoming more common in the banking industry.
Easy learning is one of Python's main advantages. Human readers may easily understand and follow the syntax. The abundance of open source Python libraries for machine learning and other applications is what gives it its power.
Select a minimum of one additional language to go with Python. Though it's far more difficult to learn than Java and even C++, OCaml is sure to attract interest. That being said, if you can write code effectively in it, you'll gain respect from other computer science nerds. Haskell and Lisp are two more languages in this area.
Select a minimum of one additional language to go with Python. Though it's far more difficult to learn than Java and even C++, OCaml is sure to attract interest. That being said, if you can write code effectively in it, you'll gain respect from other computer science nerds. Haskell and Lisp are two more languages in this area.
Still, are you truly interested in learning a language that is really obscure? For the higher frequency part of algorithmic trading code in finance, we employ C++ and Java for wide decision-making. In specialized research contexts, languages like R and MATLAB are employed, whereas Java derivatives like Scala are used for data ingestion. These languages are in decline.
Therefore, the languages you decide to study should align with the type of banking technology profession you want to pursue. Python is always a good choice, but your second language will be different. Learn Java if you wish to work with trading execution algorithms. Learn C++ if you wish to work in the field of derivative pricing. You could also learn Javascript if you wish to deal with user interfaces (UIs). There's also Kdb/Q if you want to work on tick-data level tasks.
Three languages are the ones I would never speak. These are Slang (too proprietary); Julia (too new); and Pascal (too old).
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