Let me provide a quick background. I spent 10 years in the military (enlisted) and I am currently employed part-time as a data scientist for a software company (West coast) while I complete my PhD in economics full-time at a state school. Yes, I know this is not an ideal situation but I am married with two young girls and I need provide a roof with food on the table; my assistantship doesn't provide enough for a family of four, either make excuses or work harder to reach your goals. During my PhD my fields will be in econometrics and international economics while taking a few extra courses in financial economics.
I am proficient in the following programming languages:
1) C
2) D (similar to C++ which I am currently learning)
3) Python
4) R
5) MySQL
6) Bash (not really a language but used to connect other programs easily)
all done in a Linux environment.
With that being said, after I complete my PhD I would like to move into a quantitative role in finance (I will be in my early 30s, if age is a factor). I am aware that by not coming from a target school I will have an upward battle. However, what should I to do to better my chances of landing a full-time offer by the time I go on the job market? Lastly, when I do begin researching, which area should I look at e.g., hedge fund roles?
Here are a few ideas I have:
1) Network as much as possible via a variety of avenues.
2) Post examples of my code to GitHub; site used for programmers as a portfolio of their work.
3) Complete CFA exams; not really sure if this is necessary for a quantitative role
4) Write for financial website e.g., Seeking Alpha
I have my work cut out for me but focusing on the right areas will hopefully improve my odds.
Thank you in advance for any input.
data science techniques haven't really been adopted in finance although it will slowly get there. The "data scientists" of finance tend to be called strategists, which can get away mostly with regression and an occasional pca.
Overall machine learning is far too simplistic to capture the complexity of finance (though it's arguable people can't either). It's not just about being right with your models, but also managing issues with timing, liquidity, and other risk concepts. Finance isn't just about being right.
Now, there are plenty of quantitative roles in finance, but given that data science is the sexiest job of our century, i'd rather be a data scientist at airbnb or facebook and spend time with my 2 children than an under appreciated risk manager chained to his desk. if you MUST work on wall street, a good in between would be in fintech, where you are really a tech company selling to banks.
Not the answer I expected; recommending not working on Wall St. I will admit that my hours (as I was full-time prior to PhD) were excellent from my perspective. I worked between 35-45 a week (nothing over that ever) with 24 December to 2 January off every year plus additional vacation time. Additionally, I made my own hours (came in when I wanted and left when I wanted with no oversight), just ensure my work was completed. Also, no dress code e.g., wear shorts in the summer if deemed necessary. This is fairly typical in the tech industry, particularly for software engineers. I will admit that my programming is not comparable to an actual software engineer. However, I proficient in the languages mentioned for a data scientist (data engineer, back-end type role).
Would my overall quality of life (based on the description I gave above) diminish in a quantitative finance role? Don't get me wrong, I am not opposed to working more, but if I am going to be making 20% (being liberal here) more but having my quality of life diminish by 50% that would factor into my overall thought process.
All this is under the assumption I could land a quant role.
it all depends on what kind of quant role you will land, however i guarantee you will be A LOT more stressed across the board in finance, especially since you're comparing to tech. A 20% increase in salary is pretty much expected unless you get into some of the less prestigious quant roles (they aren't bad though), with a very variable bonus. I think the main thing you gotta figure out is what quant role you'd focus on.
Some quants are just software engineers, others are more like economists. Some focus on risk, others on derivatives, and others on trade execution.
First of all, thumbs up for all the programming skills - I have been trying to expand my skillset in the area lately.
Second, as nontargeted pointed out, Data Scientist is indeed one of the 'sexy' positions in the 21st century and I am pretty sure that at a decent company your salary will be more than sufficient. If I was you, I would stay on this path or consider Software Engineering (for which you would have a solid background, given that you are truly proficient in the listed languages). Although, I think that as a Data Scientist you are going to be better off in terms of income.
Best of luck!
Thank you for the response. Granted as I stated above not the answer I expected.
Do you believe utilizing the quantitative background paired with programming I would find more interesting/challenging work as a data scientist compared to a quantitative role in finance?
You also mentioned income, factoring in cost of living, do you believe data scientists make more (considering you could also have equity in a company on top of $100k - $150k salary?)
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