Even though it is lesser known, would you say it is worth it to pursue rather than going into the common MS CS?Easier requirements to get admitted into MS CS. Broader appeal while MFE is a niche and little known degree.
By the same token, isn't it the same odds of landing a CS role in FAANG? Also, if I land a MFE at a decent college like Georgia Tech, won't I have a minimum guarantee role from which I can work upwards?I have both and the MFE degree set me up for my career in finance. I did it in the mid 2000s where quants were not a trend on social media.
Hard to give a definite answer since lots have changed. AI may make CS an obsolete degree in the future. At the same time, there are ways more MFE graduates these days and many of them couldn't secure a job. For every quant job, there is a thousands applicants. That's the odd you have to keep in mind.
For quantitative risk roles, what are the salary prospects through the career; it is possible to get 250k+ salary 5 years down the road.If you have a realistic expectation for job profile that matches your profile and get into programs with demonstrably career placement in those roles, it's a good call.
Example, if you are interested in quantitative risk roles, NCSU has good record placing graduates in banks in Charlotte area. It will be an example of knowing what you want and finding a programs that deliver.
If you aim for a quant trader, quant researcher roles at a prestigious firms (Jane Street, Citadel, etc), very few graduates will get those roles. You have to be extraordinary.
It all comes down to knowing yourself, what you can excel and optimize the path.
To become qjuantdev, would you suggest getting MS CS or MFe in a school that emphasize cs/fintechQuant dev, fintech, any roles where compensation is not tied directly to PnL.
Below is a sample of compensation data collected through r/quant sorted by firms/location/role/YoE/etc. This will be updated over time as more data is available.
Disclaimer: No guarantee of accuracy is given. The data is self-reported so it may result in sample bias.
Nonetheless, these are real-life data that is hard to find.
- Andy Nguyen
- Replies: 10
- Forum: Career Advice