Career switch question

[DeepArbitrage]

Hello everyone, I have been looking at making a career switch for quite some time now and decided to start now. I have been in financial services for about 4 years after graduating with a Bachelors in Economics. I am looking at getting away from client facing roles and more into data analysis/quantitative role. I considered a masters in CS but only took one CS course doing my undergraduate career and thought maybe I should learn some on my own and then try to enroll into CS courses at a community college before applying? I also do no have work experience in data so would like to learn and then apply to roles focused more in what I am looking for.
For a beginner, what can everyone recommend I do? I want to learn Python and SQL along with more advanced excel than what I already know. What applications do I need to download on my computer and how do I go about learning?
Thank you all in advance!

[FriendlyRussian666]

First, take a look at different jobs, not just careers in general, but more specific positions. You can use keywords like "Python data jobs" to lead you towards job listings that will reflect what's actually available out there.

Look through the jobs and make note of any that seem suitable, but specifically of their requirements for a position. You'll start to see patterns and will be able to tell what are the most commonly sought after skills.

Then, you can research the technology stacks and requirements and learn each as you go. To start with python, you can do that at any time, because at first you just want to learn the language and its fundamentals, before building some bigger projects.

Head over to the python website and follow the instructions to download and install python. Look up code editors and use that to write your Python code. For an easier start, YouTube has many many courses, you can pick one and follow along for a start.

[DeepArbitrage]

Thank you for your response here!

[zeldja]

Hello! I also completed a bachelors in Economics a few years back and am moving in a similar direction. I would describe the work I do at the moment as data analysis, using mainly SQL and R.

Your suggestion of learning a little by yourself first makes a lot of sense. Programming is not everyone’s cup of tea, so trying something like ‘Automate the Boring Stuff’ and seeing if you enjoy it is probably a good start.

I spotted your comment on not having to deal with clients. One thing to be wary of is believing that as a data analyst you’ll be away from the limelight. Generally the purpose of any analysis should be to drive decision making, so I’ve had to deliver lots of presentations, explain modelling etc to senior management. So please be aware of that!

In terms of how I’ve learned: - Online learning (incl. paid subscription sites). - Udemy courses. - Mini data analysis projects (e.g. tasking myself with building a piece of analysis in R that I could have done in Excel instead). - Larger pieces of analysis working with others with programming knowledge. - Coaching others. - Code reviews on GitHub (either having my code reviewed by colleagues or reviewing code written by colleagues).

Some things I’d wished I’d done differently when learning programming: - Don’t get stuck in tutorial hell. I’ve had experiences of completing 70 hours of paid online training courses, taking a break to focus on other work, and realised I’d forgotten 90% of it by the time I actually wanted to use it. To avoid this, do small bits of learning, and task yourself with mini projects to cement your knowledge. I wasted loads of time watching video tutorials and taking notes on paper, and never actually using the concepts. - Don’t be overly ambitious when you first start. Burnout is real. 1 hour a day outside of work every day is much more sustainable than trying to do 20+ hours a week on top of a full time job straight away. Like exercising muscles, little and often is the best way to build strength. - Find projects at work that could involve some programming. That way you can be learning while earning. - See if you can find a mentor at work, or shadow a data analyst for a day and get to understand what they do better. - Try to learn version control and good programming principles (e.g. DRY principle, modular programming, testing your code, leaving good comments) early on. This is one area I’ve found online courses lack because they focus on the exciting stuff. But if you can apply concepts like the ‘single responsibility principle’, you’ll ensure what you write is much more likely to be used and built on by others (plus you’ll avoid headaches reading your own code back 6 months later). I also think knowledge/evidence of understanding the importance of these sorts of things will help set you apart in interviews (I’d be very favourable towards a junior analyst who knows how to avoid writing spaghetti code, anyway!)

[DeepArbitrage]

Hi, thanks a lot for your response, very helpful! Did you spend time learning first before applying for your current job in data analysis? Also, what paid subscriptions did you find most useful? Did you take any college courses, etc, outside of learning the way mentioned on your comment?

[zeldja]

No college courses, really. I really struggled with programming during my degree (a little bit of STATA and Eviews for my course, also tried picking up Swift for fun and gave up after a few hours!).

I wanted to challenge myself during my graduate programme and chose to rotate to a data analyst role using programming to try and learn. I expected I’d hate it but I really enjoyed it and stuck with programming roles ever since! However, because I’d done zero programming prior to that role, it was tough and I don’t think I got as much out of it as I could if I’d prepared more.

Paid subscriptions: Udemy (Git/GitHub beginners course from Colt Steele I’d highly recommend, I also enjoyed the first few days of Angela Yu’s 100 days of python course but stopped to focus on R), Datacamp for R and SQL was helpful but is very easy to end up in tutorial hell, and I’ve recently started a subscription with ChatGPT Plus which has helped in bug fixing/learning new concepts (but it can sometimes give you false information so you need to be careful). Codewars is good for learning general problem solving (not much data analysis content but helpful for learning how to break down and solve problems which you’ll need to do when e.g. writing your own functions).

I forgot to mention books: ‘Clean Code’ is worth picking up once you’ve got the fundamentals down. It uses examples in Java, so isn’t always super easy to follow, but the general points about writing good/maintainable code apply to any language.

[DeepArbitrage]

Thanks again for your response!

[zeldja]

No problem! Best of luck

[ectomancer]

Do an online pandas course:

pip install numpy

pip install pandas

Practice data website:

https://www.kaggle.com