Breaking into S&T: Python Projects
Currently prepping for S&T 2028 SA recruiting, I know Python has been a lot more emphasized as a skill in recent years, so how can this be expressed beyond just major?
Would python projects be helpful? I'd imagine they fall into the trap of just seeming very amateur given that its hard to make anything applicable to a desk without actually working on it. For context, I'm a finance major w/ a stats/data science minor
Any insight would be very helpful, just want to know how to prepare beyond typical S&T prep
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On my S&T summer knowing Python was a big edge for sure. On the desk I got a return from 'can you code' was the first thing on of the MDs asked me and I built an inflation forecaster - that undeniably sucked - but the knowledge/ability to do it definitely helped. I would say inflation related stuff is could because a) it shows interest and b) every desk cares about inflation. Maybe pick a subset of inflation like core CPI foracasting in EUR periphery countries, etc.
If you are interested in projects do a weekly global macro/economic summary for sure, that's what every desk makes interns do, it shows real interest, and you will be so much better prepared for interviews. Should only take an hour each Saturday morning or whatever. Good luck
thank you! This is really helpful.
i just wrapped up recruiting this past cycle and I'd def say having projects on your resume gives you a huge leg up. I had a horrible GPA but I would def say my unique projects helped bump my resume up on the pile. Interviewers were always really interested in a lot of the ones I had on my resume and asked me a lot about them. I even had a recruiter on a screener that I had tell me that my resume was the only one in her pile that had a python projects section.
piggybacking off of the AN1's comments above but I would say to start off with small scripting projects like that but once you're more proficient in Python, I'd go a little deeper with the depth. For example, my resume had a project that implemented a Bayesian-Markov regime classifier to the S&P500 and a linear reg model paired with a K-folds CV method to find signals in the crypto market in a crypto trading challenge I found on kaggle.
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