Fundamental to Quantimental?

I am a fundamental research analyst at a long-only but have been learning how to code on the side. I've been enjoying coding quite a bit and ended up applying to a computer science (master) program and was accepted. 

What I am trying to figure out is if there is demand for talent that has a combination of experience as a fundamental analyst as well as the technical background to do quant work. Ideally I would like to use both of my skillsets. 

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I work in alt data at what I consider a good seat (officially a part of investment team + a lot of room for growth + scaled HF (non equity). However, I just joined the industry and also got the sense during recruiting that there is large variability. Would be curious to hear your thoughts. My current view is:

1. MM platforms with central alt data teams: Not good but potential way to break in and eventually get a better seat

2. There are some pods where they are either all Alt Data Scientists or at least are considered an important part of the pod. These are close to ideal and very, very difficult to even know where to find/look.

3. SM hedge fund data role: middle office team that is not a good role, but again more of an entry point if you don't have other options

4. SM Hedge Fund Data Role: front office team that does take data seriously (many Tiger Cubs). Still a lot of variability on if the fund takes the data seriously

5. Alt data vendors are a good way to break in and then get a lot of interviews. They are bad training for python work (mostly SQL from what I can tell) + investing mindset though, so you need to study on your own.

Important consideration is also budget. You can have a 1B hedge fund tell you that they take data seriously, but if they aren't willing to shell out >5M on datasets, your impact is capped by dataset availability.

 

Could you share what resources you used to learn how to code? Thanks.

 

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