Should I get my CFA or learn data science?
Currently a research associate at an asset management firm. My firm sponsors the taking of the CFA but it is not required. It would be great to solidify the fundamentals of the job. At the same time, I am thinking about doing an online masters in data science as a way to leverage alternate data, scale up idea/signal finding, and automate workflows. Alternatively, if I get laid off from my job, having this masters would help me become more versatile. I did not study CS in undergrad but I was always decent at math. Any thoughts on which option is better?
Both the CFA and a master's in data science offer distinct advantages, and the choice depends on your career goals and current role. Here's a breakdown based on the most helpful WSO content:
CFA Pros:
Data Science Pros:
Considerations:
Recommendation:
If you’re looking to balance both worlds, consider starting with the CFA (since it’s sponsored and directly relevant to your role) while simultaneously learning coding basics (e.g., Python, R) through online courses. This way, you can test your interest in data science without committing to a full master’s program. If you find data science aligns with your interests and career goals, you can pursue the master’s later.
Sources: Q&A: Managing Director at Large Global Asset Manager, Non-Target Undergrad to Non-Target Grad to Asset Management, Q&A: Managing Director at Large Global Asset Manager, Lateral to Quant PM - MBA, MS Data Science, or MS Finance?, https://www.wallstreetoasis.com/forum/asset-management/transition-from-data-science-to-asset-management?customgpt=1
Bump
I would do the CFA level 1 which is fairly easy for someone in finance and I would also do the online Master's. I believe there is great value in having interdiscriplinary thinking and the majority of people who came up with something creative or interesting in finance often come from other fields or got exposed to other fields, which prevents them from having a tunnel vision of the field. You can borrow or have better "mental models" after even a slight exposure to how some data scientists think and see the world. Furthermore, with the raise of quanitative analysis and AI, I believe that lots of things can be delegated to a machine, leaving one more time to do more complex intellectual analysis - which is where the mental gymnastics of the CFA would prove very useful; and contrary to more mundane analysis that for instance you could hand it to an AI (e.g., do some 10-K screening, analysis, etc.), I doubt you could delegate data analysis to a model because you wouldn't be able to assess the result if you don't have a foundation in it. Stated differently, AIs can do some financial analysis and you can follow it because they can explain you that this is based on a formula and will explain why it's appropriate or not with almost no degree of variations in formulas, but it might be impossible to assess the results of a model if for instance the model itself is unaware that based on your data it is over-fitting the results, and thus, leads to highly biases analysis. Moreover, if you're giving recommendations or analysis based on data, you might as well be confident in the quality of that data or its shortcomings, which someone without a data science background might be blind to it. Good ideas also come from reading fresh ideas across academic papers, so having some foundations in it might allow you to explore ideas that are yet not widespread across the market and thus benefit from a "first come first served" basis by employing or tweaking some ideas those academic papers share - which again, someone who just understands data science in the limits of its application for its role will be first off, unprepared to digest those, and second off, not as inclined or interested to read them due to the ideda that you're inclined to want to master those things which "you consider you're familiar and good at".
Thanks for the detailed response, I really appreciate it. Out of uriosity, why do you recommend just taking level 1 of the CFA and not 2 and 3? Also, in terms of hiring, would your average portfolio manager prefer a research associate with a CFA or a data science masters?
All 3. I said just level 1 because it's easier and not too distracting on top of working and studying. If you can prepare for level 2 while doing the master's more power to you...
CFA preferred. If they needed a data scientist they would take someone with a strong STEM background or quantitative experience. An online degree wouldn't be considered. The only reason to do it so to become better at investing/researching as you could leverage data better than someone who has a more amateurish approach to it.
Got it, thanks. I figured that a PM would take on a data scientist with a dedicated STEM background but I was wondering if having the degree would be an adding advantage when it comes to recruiting given how much of the junior level work is essentially business analytics.
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