Math What Math-Intensive Careers Make a Social Impact?

[zooxanthellae]

I'm an undergrad majoring in math. I like it for the generic reasons that math-majors like math, but I'm concerned about what I'll do for a career. Ideally, I'd like to do something that is "useful". The vague, dim ways I've conceptualized possibilities as an undergrad is epidemiology or majoring in math-econ and doing consulting work for nonprofits. On the other hand, I'm not entirely sure those ideal jobs exist.

Tl;DR: What are math-intensive jobs that will let my assuage my Catholic guilt?

Thanks.

 

[lisab]

Nice that you're considering these issues in choosing a career!

As far as I can tell, epidemiology is still a viable field. Nonprofits are a good option as well. Perhaps you could contact one near you, and ask for an informational interview?

Have you considered teaching?

 

[chiro]

I'm an undergrad majoring in math. I like it for the generic reasons that math-majors like math, but I'm concerned about what I'll do for a career. Ideally, I'd like to do something that is "useful". The vague, dim ways I've conceptualized possibilities as an undergrad is epidemiology or majoring in math-econ and doing consulting work for nonprofits. On the other hand, I'm not entirely sure those ideal jobs exist.

Tl;DR: What are math-intensive jobs that will let my assuage my Catholic guilt?

Thanks.

Hey zooxanthellae.

The big rule of thumb that I would use is 'anything applied'. Now this might seem like an easy distinction to make but it's not.

The truth is that in the above context: number theory is applied because its used in security applications. The fact that people (a lot of people) make use of it makes it 'applied'.

Statistics is a huge one. It's used everywhere: it's used for health, government, finance, business, basically anywhere where there is data: and there is a lot of data. In fact the problem has gone from "Where do we get the data?" to "There is so much data! How do we make sense of all this data?": this is why there is such a big demand for anyone that can analyze data and that usually means statisticians, mathematicians, computer scientists, linguists, psychologists, biologists and lots of other people working together to try and make sense of whatever data in a given context.

But having said the above, if you have the training where you can pick up a new book that covers computer science, mathematics, and statistics then you'll be able to work in a lot of places. If you can learn quickly, and do your job, that is good.

The truth is that things are changing so fast in this world now, that people not only have to go to university and get an undergraduate degree, a masters degree and maybe even a PhD, but they have to keep learning on the job probably for the rest of their lives in some professions.

This is showing how we are going from an industrial economy to a knowledge economy and this is a very big challenge for businesses because they need people that can learn quickly enough on top of doing something that makes use of their prior training.

Finally with respect to a career, the above will help you with getting a career but it's not the only thing that should be considered.

The above was trying to give you an idea of some areas of mathematics that are 'applied' in major ways, but there are also things that are not technical that are important. Things like attitude, ability to do things you don't want to, and working with other people are very important as well.

One my gauges for useful is basically 'how many people make use of something directly or indirectly?'. Also it's better if you can tell a layperson how they benefit and see if they agree. People know that computers are useful, they know that Google's useful because they can find info quickly: no technical stuff just easy to understand in a basic way. This is all IMO, but if you explain what something is in a basic way to a non-specialist and they have trouble understanding why something is useful, then chances are it may actually not be useful. It's not a perfect gauge of success, but in order for something to useful people have to make 'use' of it so yeah.

I can't see how you can go wrong with anything that has any 'applied' mathematics, presentations (both oral and written), computer work of some sort (programming, modeling, etc) and (this is important) projects where you have to give a report or analysis to explain technical results in a non-technical way.

 

[zooxanthellae]

Nice that you're considering these issues in choosing a career!

As far as I can tell, epidemiology is still a viable field. Nonprofits are a good option as well. Perhaps you could contact one near you, and ask for an informational interview?

Have you considered teaching?

Sorry, what's an informational interview? Just an actual interview, where all you do is ask them questions? I'm mostly wondering about how math would even be applied, here. It seems like it would be more business math than anything (of course, it is unrealistic to expect applications of topology or something, but the more abstract the better).

I have considered teaching, but I doubt that I have the patience to teach at anything below the college level. That, in conjunction with the rather messed-up state of our school system and my desire to do something besides pass on information, makes me wary of teaching.

@chiro: Right now I think I'm going to pursue a pure math major since I really dislike differential equations. However, that is not set in stone and I'm going to discuss it with some people in the department. Either way I hope to take several theoretical comp sci/algorithms courses, so it won't be totally pure.

The trouble is my conception of what these sorts of jobs would entail is pretty cloudy. When I imagine an ideal career, it involves something like me figuring out a new, sexy mathematical model for the spread of a disease, or creating a new algorithm to manage the supply chain and distribution of retrovirals in impoverished countries. Does this push me toward statistics over math?

Really, what I'm talking around is that the best place to go for someone who wants to make a living doing interesting math (outside of academia) seems like Wall Street, and I'm very ethically conflicted about doing that. So I'm looking for similarly mathematical, but more "socially useful", avenues.

It would be interesting to talk to someone who has a career near this description.

 

[MECHster]

I encourage you to study basic economics. For profit businesses raise the standards of living. In my opinion, companies like Intel or IBM have done more for this world as a whole than say, Mother Theresa.

 

[lisab]

Sorry, what's an informational interview? Just an actual interview, where all you do is ask them questions? I'm mostly wondering about how math would even be applied, here. It seems like it would be more business math than anything (of course, it is unrealistic to expect applications of topology or something, but the more abstract the better).

I have considered teaching, but I doubt that I have the patience to teach at anything below the college level. That, in conjunction with the rather messed-up state of our school system and my desire to do something besides pass on information, makes me wary of teaching.

@chiro: Right now I think I'm going to pursue a pure math major since I really dislike differential equations. However, that is not set in stone and I'm going to discuss it with some people in the department. Either way I hope to take several theoretical comp sci/algorithms courses, so it won't be totally pure.

The trouble is my conception of what these sorts of jobs would entail is pretty cloudy. When I imagine an ideal career, it involves something like me figuring out a new, sexy mathematical model for the spread of a disease, or creating a new algorithm to manage the supply chain and distribution of retrovirals in impoverished countries. Does this push me toward statistics over math?

Really, what I'm talking around is that the best place to go for someone who wants to make a living doing interesting math (outside of academia) seems like Wall Street, and I'm very ethically conflicted about doing that. So I'm looking for similarly mathematical, but more "socially useful", avenues.

It would be interesting to talk to someone who has a career near this description.

Yes, that is what an informational interview is. The objective is not to get a job, but to gather information. Given that your conception of your future career is a bit cloudy, talking to someone in the field could give you some insight.

If you're wondering how to set up an informational interview, try talking to your professors to get an industry contact from them.

 

[chiro]

@chiro: Right now I think I'm going to pursue a pure math major since I really dislike differential equations. However, that is not set in stone and I'm going to discuss it with some people in the department. Either way I hope to take several theoretical comp sci/algorithms courses, so it won't be totally pure.

The trouble is my conception of what these sorts of jobs would entail is pretty cloudy. When I imagine an ideal career, it involves something like me figuring out a new, sexy mathematical model for the spread of a disease, or creating a new algorithm to manage the supply chain and distribution of retrovirals in impoverished countries. Does this push me toward statistics over math?

Really, what I'm talking around is that the best place to go for someone who wants to make a living doing interesting math (outside of academia) seems like Wall Street, and I'm very ethically conflicted about doing that. So I'm looking for similarly mathematical, but more "socially useful", avenues.

It would be interesting to talk to someone who has a career near this description.

If you going to do analytic work then you have to take into account not only the kind of work you do, but who you are working for. Let me explain:

If you are a programmer, working for another programmer then your role is going to be a lot different than being say a programmer that is working for a manager who isn't as technically oriented.

The programmer working for a programmer will be able to speak to their boss in a way where they do not have to think about dumbing down their jargon and language as they pretty much speak the same language. Furthermore the programmer boss will understand his subordinates work and the focus will be completely different.

Now if you are an analyst working for a non-technical specialist then that's completely different. You may have to give presentations with jargon that your boss understands and probably have to give the kind of information that they expect. You will need to learn what's important for your boss to know because usually if you are doing some kind of technical work, it's going to be for your boss to make some kind of decision that takes into account your work and more importantly your advice since they probably don't have the time, (even if they had the technical skills) to do it themselves: it's not their job and it's why you are hired in the first place.

So once you understand the work environment, who you are working for (not just the company, but the actual person(s) that you report to), then that will give you an idea of the kinds of things that you need to pay attention to.

If you have to work with people with a different focus or with different backgrounds (boss and other coworkers), then being able to take technical analysis and translate it into another 'lingo' is very crucial. If you can show at the interview that you can do this, then if this is the norm they should pick up on that.

All of the above is on top of anything analytical and technical. The technical and analytic stuff is important, but it's important to realize what the actual job is all about (which is one of your questions). The above should give you some hints to pursue for you yourself to answer this question.

With regards to Wall street I have a few comments about that of which most come from reading other people's comments both here at PF and abroad just so you know where I am coming from.

I used to think that all of finance is scandalous and bad. I don't think that anymore. I also used to think that all investment places are bad. I don't think that anymore.

What I have found is that a lot of people in the financial community are actually concerned with things like fraud, collapse of economies, and maintaining the integrity of the financial system.

The truth is that the financial system is important for everyone. The cattle ranchers need some kind of security when they go to sell the cows and futures are helpful for that. The guy that needs capital to run a business that gives consumers what they want, that hires people giving them an income, and that let's those workers provide other businesses with inflow themselves is a good thing and a lot of people are in favor of that.

There are people in finance that like capitalism: they like it when the guys and girls that provide something useful are rewarded and the people that don't cut the mustard are not and subsequently go out of business.

There are also people in finance that don't like fraud and don't act fraudulent themselves. People in finance want confidence in their systems because when you don't have confidence, bad things start to happen not only for us laypeople but also for them. Confidence is a really integral part of the system and it's not only important to have 'confidence on the surface', but also 'real confidence' because people that know better will react to situations where there is no 'real confidence'.

I guess what I'm trying to say is that you shouldn't paint everything with the same brush. Chances are if you pay attention and keep a clear head, you'll know if something is not right and then it's up to you to either say "Thanks, but no thanks" or to keep going and go down the rabbit hole and end up convincing yourself that 'things aren't that bad'.

You will have a lot of choices to make which will narrow down things as you go along, but hopefully the above advice is somewhat useful for you to help in that decision making process.

 

[mal4mac]

Try reading "Thinking fast and slow" by Daniel Kahneman - it's not (very) mathematical but gives a great overview of areas in psychology and economics where mathematics is used, with references to more mathematical works.