[peterhalburt33]

As a mathematician who works with many engineers and computer scientists, I wanted to expand on one of the points under the “Getting a Job” section. While it is certainly true that a mathematics education provides a great background for understanding other STEM fields, I would caution math Ph.D students who expect these jobs to be open to them because of their STEM connection: the onus is completely on you to bridge the gap between what you do and the field you want to work in. While it may be true that someone will hire you for your critical thinking skills (though I will personally say that I have never seen this happen), it is more likely that your deep specialization in a tangentially connected field (coupled with not being involved in the culture/conferences of the community you wish to enter) will be an impediment to entering a new field: you expect to be paid like a Ph.D., but will potentially require years of training to get up to speed.

As an example, I remember the advice of “just go into data science” being handed out like candy to students interested in industry around the time I was in grad school (10 years ago). To be sure, there was a period where a STEM background + interest could get you in the door, but that time is over. These days you are competing with many equally brilliant students who have taken multiple courses and done research in this area, and it is highly unlikely that an employer will take a chance retraining an e.g. algebraic geometer with no precious data science experience to suit their needs.

All this to say, if you have an interest in another area, you must know the players and their work in that area while simultaneously knowing your area in math. It is not easy by any means, you are essentially signing up for twice as much work learning your field and theirs, but the rewards are great - as a connector between two fields, you have precious expertise that is very employable across a broad range of industries (my first job out of grad school was essentially providing advice on research programs helping connect different STEM communities to government funding agencies, but I was able to use my connections from that job to get back into research).

[mmmmpancakes]

I want to re-frame what you're saying slightly.

Yes, the onus is on you to learn the skills you need to show up and produce on day 1. That's 100% true and it is a lot of work. Having a math phd alone and interest is not enough.

However, there are still plenty of paths from math phd into data science and adjacent fields. Those courses you mention are things that someone with a math phd can 100% self teach, almost certainly to a level of understanding that is stronger than someone coming out of a DS masters. Learning how to interview on those concepts is important but ultimately they are very easy for a math phd once they know what the rules of the game are.

Personally, I spent the last year or so of my postdoc obsessively leetcoding and doing side projects in DS and landed a non-entry level data science position as my first job out of academia at a FANG. This is with a pure math research background totally unrelated to the position.

So it is still very possible. I think painting it like you do is a bit pessimistic and will discourage the wrong people. From personal experience, I saw comments like yours over the past year while I was job hunting and found them very discouraging.

The most important things are:

- have a network of similar people who have also made the transition (recently!) to get good advice and maybe also some referrals. These are the people you met in grad school a few years ahead of you.

- know exactly what type of position you want (or converge quickly) and focus on it relentlessly.

- understand the value you bring and the value others perceive someone like you to bring. Talking to people in hiring positions for different roles is the fastest way to learn what you have that is valuable. Do that as much as possible. Then you can line up how you value yourself with how a hiring manager values you, which will be the happiest result.

- take as many interview opportunities as possible to get that interview experience.

- Work relentlessly to interview better than those people from DS masters or whatever other sources they might come from.

[BossingAround]

> the onus is completely on you to bridge the gap between what you do and the field you want to work in.

Yes, like for everyone else. Sounds like when I was getting into the field with no formal comp sci education, only I was expecting this to be true :).