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Not Excel But Python Is The Answer If You Want A Banking Job Now

Updated: Sep 22, 2021


Python Training

Recently, I spoke with a friend of mine which is an HR and he told me that he was astonished a few years ago when interns he hired had never used Excel before. They were incredibly bright, but Excel had never been a part of their academic careers. It was unusual at the time. Today, everyone they hire is not just familiar with Excel, but also with Python programming.


In the financial industry, there has been a generational transition. This sector has traditionally relied extensively on Excel. Excel was used to build processes and was the main tool that underpinned everything. However, as data has grown in volume and complexity, the technologies for extracting and analyzing it have evolved. When data is stored in secure old databases, Excel becomes obsolete. If you wish to use these databases, you'll need to know how to code. Excel is still utilized, but only as a backup.


The recent grads, on the other hand, do not use Excel at all. They use Python (or R) to automate their operations and distribute the results via email, intranet, Excel files (without having to open them), or PowerPoint. Excel has become a symbol of inefficiency and bad coding skills. Yes, many firms still rely on macros and Excel reports, but as businesses shift to cloud server storage, this is increasingly being phased out.


As a result, if you're seeking to break into the banking industry right now, Python is the talent you'll need. Python will help you find work in the financial business, from sales and trading to portfolio management and risk management. It's the one quality that sets applicants apart during the hiring process.


Being able to code in Python is advantageous for a variety of reasons. Let's pretend you're a market risk analyst or even a trader. The information you receive on a daily basis comes from a variety of sources. You gather pertinent data for analysis and may combine it with other data in Excel to create charts or explain trends. However, you must use the company's front end systems to get the data to compile. Because they communicate with the data warehouse and servers to offer information to the user, these systems are referred to as UIs (User Interfaces). So, what if you want to look at a correlation between two different sources of market data? - Then you discover that because the UI was designed years ago, this second source hasn't been programmed into it. The process of updating the UI to reflect your new requirement has the potential to be time-consuming. However, you may access the data from the database without modifying the UI by using an Application Programming Interface (API). Everything is protected in an API, yet it is still accessible without the limits of a pre-programmed UI. The versatility is huge if you can leverage an API. Someone who wishes to immediately correlate market volatility between two previously unrelated variables, for example, can create a piece of code and directly access the API. This is the potential of the fresh graduates we're bringing on board.


After all again, old people like me and my friend continue to utilize the old UI and export data to Excel in order to build charts. But it's clear that it's inefficient when you can just develop some code that accesses the API and, as a result, automate the creation of a daily chart that's sent through email before we even get out of bed. The flexibility is huge, which is why organizations need to hire juniors who are familiar with the process or enrol in Python training or classes for the existing employees.


Some students are still unaware of this. It can be difficult to locate programmers that want to work as a trader in a front office team rather than in a technical support role. Many computer science graduates believe they should apply for technology jobs, however, this is incorrect. Organizations are in desperate need of coders on the trading floor right now.


This isn't to claim that all of the new recruits are Python programmers. Organizations still bring in odd exceptions, like the interns who didn't know Excel a few years ago, but it's usually because they have another ability that's judged equally or more significant. - However, there are significantly fewer of them now than there were previously. As I mentioned earlier, organizations may enrol in Python training for their existing employees and new recruits.


 

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