MS in Mathematics, having trouble finding work outside teaching algebra

Question

10 years ago, I got an undergraduate degree in IT/CompSci from a good school. I spent most of my hours playing video games or drinking beer, and learned only enough to get a barely passing GPA. I never used the degree, as I joined the military and did the minimum amount of time for my paid education and got out.

7 years later, in 2016, after traveling and busing tables for a couple years, I realized that I had been wasting my life. I realized that learning is cool, and that I'd wasted a great opportunity both to learn interesting things and to have a rewarding career. So, I decided to go back to school.

I applied the graduate Math program at WVU, for no other reason that I got a B in Calc 2, one of my highest grades in undergrad. They let me in even though my undergrad GPA was abysmal (2.5 or so), and that I didn't have any of the prerequisite math classes to get in. I agreed to spend the first two semesters taking undergraduate differential equations, basic linear algebra, proof writing, etc. After that, I started taking a full load of graduate courses. After three years, I survived to get a piece of paper, but having retained little actual mathematical ability.

I was exposed to a lot of math, but because I was so far behind the learning curve, very little of it stuck. I was too busy trying to pass/survive to be able to learn much. What I did pick up lies mostly in the realms of numerical methods and differential equations. It is important to note that I learned almost nothing, even in these two areas. I graduated this summer, and can only talk in very vague terms about what I was exposed to.

Now, I am unemployed and wondering why I ever gave up waiting tables. I can program a little. I can read a math textbook without my brain exploding, and that's about it.

Now, I spend about 10 hours a day reading textbooks on ODEs and Numerical Methods, as well as working practice programming exercises from Project Euler and sites like it. I'm slowly working through Khan Academy's probability and statistics courses, as I never learned any of that in school.

It's dismal. I'm depressed because I worked so hard to try to bring myself up and correct a life time of laziness. I'm still working at it every day. My wife goes to work, and I read until my eyes bleed, occasionally checking my email for the most recent employer rejection letter. Now it seems like I should never have left waiting tables.

So what's the question here? This:

What do I do? What do I study, and how long is it going to take before I know enough to be marketable?

I can teach community college, but the thing is i loved the stuff that was covered in school, and I want to apply it. Sad thing is, I'm too dumb to get a job at anything but teaching algebra to bored college kids who don't want to be in class.

Answer 1

First of all, jobhunting s u c k s. It sucks even more when you're trying to get into a field and it sucks further if you're not in a major metro area. It's a massive timesink with terrible ROI, but it needs to be done in order to get a job at all. The truth is that whether you get hired isn't going to just depend on your skills and experience, but also on whether the person reading your résumé thinks your skills and experience line up with what they think they want, and you don't have a lot of control over that. So honestly it's impossible to predict how long it will take before you find something.

That being said, your situation really doesn't sound so horrible to me. You're interested in and studying things that (1) you want to do and (2) employers are looking for. You have a master's degree in a marketable field. As for whether you feel you learned much during your degree, it sounds to me like you're just in a bad place with a killer case of impostor syndrome. Some employers might want to see your transcript, but they're a lot more interested in what you can do for them. So maybe try putting together a portfolio of the kind of work you want to do, which might include models or software that you developed or small projects that you did for free or for cheap for someone. (These are pretty standard suggestions.)

Finally, you can't be everything to everyone. It might feel like you need to cast as wide a net as possible, but it sounds to me like you might be spreading yourself thin and that's contributing to your frustration. Narrow it down some by considering where your best bets are in your geographic area and what you really want to do. For example, if coding is the right path, then back-burner the modeling, or vice versa. Good luck.

Answer 2

Get a job. Don't do more studying - you already indicate that you 1) are not good at it and 2) don't have a good reason to do it (you would effectively be doing it because you're avoiding the job market). It doesn't matter how much you love the topic if you're terrible at it. In fact I would question that you actually love the stuff because if you do, how did you learn so little?

So: figure out what you're good at + don't hate doing, and get a job there. Make use of the job-seeking resources you have at your disposal, e.g. WVU has a career services division, go talk to them and get their help. Stop reading about ODEs and start reading about how to navigate the job search process. Talk to your wife - she's got a job, that means she's done something you haven't.

One more thing - do some critical thinking about what you actually learned during your MS. If someone hires you, what can you contribute? If you go into an interview genuinely thinking you can contribute little, it's not surprising that you're getting rejected everywhere.

Answer 3

I was in a comparable situation a few years back: I was stuck on a CS BSc thesis that wasn't going anywhere fast with an obscure and unmarketable topic. Also, I had no relevant work experience. I managed to improve my situation through a couple of different things.

The best way to get a job is to have a job

Finding a perfect job rightaway is hard. All the nice jobs require prior experience. So clearly, you need to get experience. Start a step lower, find a job that will take you, and then work your way up to something you like for the long term.

I got my foot in the door by working for an IT secondment firm that mainly hired STEM students with "stuck" degrees, like people dropping out of a physics or engineering bachelor in second or third year. They were smart people with problem solving skills but no nice employable diploma. They made amazing helpdesk staff: competent and cheap to employ. For me, it was a good entry to the job market; I got to get used to working in a big company, and I pursued the internal training opportunities.

I then pursued internal trainings in the secondment firm, which both gave me new skills but also brought me to the attention of senior colleagues who then knew what kind of gigs to put me on, which eventually landed me in a nice junior development job.

Evaluate what skills you have

Reset your mind. Try to find out what marketable skills you have. There may be more than you know.

• You've gained soft skills while waiting tables.
• You've spent time in the army, learning both physical skills but also discipline.
• You've actually managed to graduate from higher, which is still higher than the majority of the population does.

This is just a start, my point is that you need to get an idea of what skills you actually have. Here are some ideas on how to find out what you already have:

• Take a whole day to browse job listings for positions you're interested in on LinkedIn and Glassdoor, and note down what skills are asked for. Then, try to find things in your background that qualify you for those skills. Finally, compose a list of the frequently asked skills that you turn out to have. Update your CV, describing in your previous positions how you learned those skills.
• Contact the career counselor at the university you recently graduated at. Most universities are keen to advertise that their graduates are successful at the job market, and provide services to help make that actually happen. Try to schedule an interview focused on exploring where your opportunities lie.
• Reach out to people you were in the army with, and have a chat with them, ask them how they've been able to use their army experience to boost their civilian career. Consider which skills also apply to you.

Treat the search for jobs as a research project

As a science grad it can be easy to think of math as a science and job searching as some sort of magic trick that other people are mysteriously good at. But in fact it's a skill, and other people have put a lot of thought into how to get better at it. So start reading up on how to be better at interviews, writing CVs and all that. Use what you've learned in university for doing research, to research how to get better at job hunting.

Find out what's missing in your skillset

Just like you need to find out what skills you already have, you also need to find out what's missing. Again, go read fifty++ job postings in a field you want to work in, and list the required skills. Count frequencies. Figure out which skills/platforms are generally asked as a package deal. Then look at which clusters you already many of the required skills for, and what's missing.

Get coding

One question that you'll get (in many forms) is "what have you actually done". For example, you mention data science as a direction you're looking at. Look for some competitions in a field you like and try your hand at some competitions. Kaggle for example (data science). You're not going to win; a lot of these teams are very practiced. But there are some real benefits for you in participating:

• When you get asked in a job interview what you've done in the field, you have something to point to. "I did this and this and this Kaggle competition and scored better each time" sounds like experience, because it is.
• You learn skills by doing that you can't get by just reading.
• These competitions have very active forums and you can learn a lot from what the other teams are doing and sharing.
• You might make some connections with other participants that can help you.

I mentioned before that the best way to get a job is to start by having another job. This is the next best thing, and it's got a huge advantage for you: you don't need anyone's approval to get in. You don't have to get hired into a competition.

Don't obsesss about certifications

There are many, many, maaaany certifications in IT. Nobody has all of them. Many people don't even have all the ones that you would think are standard for a particular job, or that get asked on a job posting. For many jobs, meeting 2/3 of the listed requirements can be enough to be considered. Because IT platforms change all the time and almost nobody uses software like the manual tells you to, so every company knows they'll have to train new employees anyway. A certification helps, even one in something fairly unrelated, because it shows you can work hard enough to get it, and it shows you're trainable. But don't worry about having all of the ones in a job listing.

Answer 4

You need to get rid of one big misunderstanding which plagues many students who "went to college to learn interesting stuff" and then failed to get a job.

Nobody in industry cares about the "stuff" that you learned in college (or what you are teaching yourself about ODEs and numerical methods from textbooks - most of the standard topics they cover were the state of the art back in about 1960, but you may have noticed that computers have changed a bit since then.)

What industry does care about is that getting a college degree taught you how to learn independently. Your college GPA might not be a very good measure of that, but it's about the only one available. It is certainly better than nothing as a measure of your ability to focus on doing what you are being asked to do (even when it's not particularly interesting or motivating), your time management skills, etc.

The other thing that industry cares about when choosing who to hire is "how much money are you going to make for us if we hire you?" Of course they don't put it quite as crudely as that, but that's what is behind everything else in the selection process.

Your work experience and military experience probably taught you a lot more useful stuff relevant to getting hired than anything you learned in college. Stop reading textbooks and start thinking hard (and/or get some professional advice) about how to sell that story to your potential future employers.

Answer 5

Get around people! A lot of people want to help you, you just have to find them.

How do you do that? Go to meetups and groups. Heck, go to church, there are a lot of nice people there. Meet people and if they seem like someone who would give a care about you, tell them about your situation. They can help you much better in person. They can give you advice that is more relevant to your situation because you can have a longer conversation with them. You may have to talk to a number of people. But the insight they give will really help give you fresh perspective that short answers on the internet will not be able to match. You will also gain friends in the process who are rooting for you to succeed. One thing we don't learn in school very much is how important other people are to our success. But often the biggest breakthroughs in our lives come when others help show us new ways of thinking that lead to success. And when you are in person it is much easier to have a dialog. By the way, good job on having the courage to reach out with a question online!

Answer 6

Suggestion: stop learning ODEs and learn Data Science. Nothing against ODEs, but there are very few jobs in that area directly. but Data Science on the other hand is very hot, and likely to stay so. And you have the background to get it faster than those that struggle with the math (and there are a lot of those even in this field), and it is a highly employable and enjoyable field.

The competition is relatively thin, There are very few degree programs still, so almost no one in the field actually has much in the way of paper qualifications. The best of course have a doctorate in Statistical Learning - and can code well - but people like that are few and far between. You having an advanced degree in Math actually gives you a leg up over most people.

Most practitioners have just completed a few Coursera or eDX courses, and played with Python and R, and discovered that they like it and can actually get useful things done. Talent helps. But still most have some kind of imposter syndrome to my experience too, so that should make it a bit easier on you.

If you are interested need more advice, let me know - I mentor quite a few junior people in this area in my company.

Answer 7

First thing: congratulations on starting to get your life together.

Many good suggestions here. I have one more. While you search for a job, consider volunteering in a semitechnical capacity for some nonprofit or political organization whose goals you support. With your IT/compsci skills (even if rusty) and your ability to think mathematically you can be useful. You will sharpen those skills, meet people who may know about jobs, and have a good item to put on your resume.

And listen to your wife.

Answer 8

If you understand math to a decent level, I think you're more than fit for a career in machine learning. Since you can also program, that's another advantage for you. The nice thing is that ML is a tool, rather than a "destination". You can use it to solve a lot of problems, from many different domains, which will interest you beyond just doing what the boss says to do.

I can highly recommend https://course.fast.ai. I haven't done it personally as they came up a bit after I already graduated and found a job requiring these skills. I looked through the course to recommend it to my pears and I learned new things myself, which indicated how arrogant I was to consider I knew enough of deep learning.

But don't listen to me. Go on Twitter and see what people say about fast.ai and Jeremy P. Howard. It's incredible. Every day I see success stories from people of all kinds of backgrounds, some who say didn't do much coding before. And then look through the forums. I'm in awe of how supportive people there are and how complete strangers help each other learn and progress while solving real-life problems.

So, TL;DR: use your math and coding advantage in a highly sought-after area by learning deep learning and applying it to new problems that are of interest to you.

Answer 9

If you have programming skills and some passion for programming, consider contributing to some existing open source project on your spare time. There are many of them, e.g. on http://github.com/ or http://gitlab.com/

If you work with others, you will learn those soft skills (communicating, working in a team on software development). And you'll increase your self confidence.

But contribute with your real first and last name, not a pseudo. You want to raise your visibility

Read also http://norvig.com/21-days.html

Did you consider getting some help from a psychotherapist?

PS. If you are able to code in C or C++, I have a crazy open source hobby project with two partners, and I am seeking for a few more of them. Contact me by email to basile@starynkevitch.net for more... (Look on my web page before... you might guess what I am interested in).

Answer 10

There are some other good answers here but none of them give concrete steps to your questions of

"What do I do? What do I study, and how long is it going to take before I know enough to be marketable?"

This is probably because these are questions that only you can answer for yourself, but based on your question and your profile description of wanting to use math and programming together, and your recent interest in statistics I think that is where you should focus your attention. Obviously I'm biased as a biostatistician but your background seems like a perfect fit for applied statistics (a good amount of math and a good amount of programming) and it's not like I'm alone in saying it's a good job either (https://money.usnews.com/careers/best-jobs/statistician).

What do I do? - If you are spending 10 hours a day studying, get a certificate or Masters (online or in person) for it. That way instead of saying I read x,y,and z, books on ODE's you can say I got a graduate certificate in Python, or something related. This is much more tangible to an employer. There are many online programs in applied statistics/ data science and the American Statistical Association has been highlighting these programs (https://community.amstat.org/blogs/steve-pierson/2019/10/21/amstat-news-qas-featuring-new-masters-and-doctoral). You will not be getting the same training as your previous masters, the emphasis in many of these programs is heavily applied, you will learn how to do machine learning with real data for example instead of learning the theory of machine learning (something you can probably teach yourself if interested/needed).

What do I study? - Based on the jobs you are applying for in your comment, stop studying ODE's and Numerical methods, or apply for jobs where the application of these methods is more obvious. You seem to want to use programming, pick a language and get good at it. I would suggest R or Python since they are in high demand and will teach you basics of programming that you can apply to other languages.

How long is it going to take before I know enough to be marketable? - Realistically at least a year, you need to have some proof you are a desirable candidate, that means degree/certificate/projects you can show off but along the way you just have to keep applying for jobs.

Answer 11

but the thing is i loved the stuff that was covered in school, and I want to apply it

I'm going to give you an outside-the-box suggestion that may or may not intrigue you: consider going into a different field where you can apply the topics that interest you. A lot of mathematics historically was developed in conjunction with other sciences to help describe the natural world. Look at Karl Pearson and Ronald Fisher and their contributions to the life sciences.

Here's how this might look for you:

1. Find a field that interests you and has a need for mathematicians. Extremely math heavy fields like physics might be harder to get into because they'll have higher base standards of math, but other "softer" sciences like sociology, economics, psychology, biology, ecology, etc, do not have that same expectation. Research in these fields ranges from very applied to very theoretical. The problem is, most people that go into these fields are not very advanced in math, so the theoretical end of the spectrum tends to be lacking. This could be your niche.
2. Go into a master's research program in said field. A master's won't necessarily give you the flexibility to do exactly what you want, but it will give you necessary background in the field and help you decide if you want to continue this route. Master's research programs are generally paid; you won't necessarily make a lot of money doing it, but unless you're waiting tables at fancy restaurants, it's probably not going to be much worse. You shouldn't have to take out loans for a MS degree doing research.
3. Then go onto a PhD program where you have the flexibility to do what you want with math. This could be applying advanced mathematical concepts in a novel way to the field you are now in, or maybe even finding a way to use your new field to drive discovery of new mathematical concepts. The pay situation is similar to a MS. Meanwhile, depending on the field, your course requirements are probably going to be flexible enough that you can probably take graduate math courses as part of your PhD program.
4. Postdocs are an optional step that may appeal to you. They give you more flexibility in defining your own research.
5. Going into an academic research position may be your end point. Here, you have the flexibility to define exactly what you want to research, how theoretical/applied it will be, and develop a lab of graduate students with similar interests to help support you while you simultaneously support and train them.

Now, I'm going to give you some perspectives/examples about this from my view as a wildlife ecologist/geneticist/programmer:

First: ecology, in particular, is interesting because it is a nexus science that incorporates virtually every other field you can imagine, including physics, chemistry, law, economics, geology, biology, psychology, etc. This means there is a lot of flexibility in how people curate their interests and careers.

Second, going into grad school, I had a strong background in computer science and well above strength in math (I've always enjoyed math and almost switched to mathematics in my undergrad). Programming and math are both very valuable in ecology, and especially rare for incoming students to have any level of proficiency (most students only have a rudimentary calculus background, if that, and no programming experience). My background has given me a huge advantage in conducting advanced and interesting research. I'm actually planning on taking some of the graduate-level math courses in things like modern analysis, linear algebra, etc, and my advisor, who is not a math person but recognizes its importance in theoretical ecology and genetics, is very supportive of this.

Third, ecology, and probably other "soft" sciences as well, tend to be flexible about the backgrounds of incoming graduate students. I did have a background in biological sciences from my undergrad, but I know people that have come from completely different backgrounds. In one case, a friend did her undergrad and masters in some form of engineering (mechanical?) and worked for NASA. She then completely shifted gears and started a PhD in quantitative ecology and had a successful degree doing black bear research. Being able to pitch a strong math/engineering background is what got her in, despite no background in ecology that I'm aware of.

Fourth, related to the previous point, it's common in my field for people to start grad school late. I started my MS 5 years after my undergrad. I know people that started their PhD's in their mid- to late-thirties. Age isn't so much a factor for developing a career in some fields like mine.

Fifth, ecology, and other sciences as well, develop many theories based on mathematical concepts. It's really common for these theories to be developed based on mathematical concepts that are decades old (or older); often they just weren't applied earlier because people with the necessary background and expertise to do so are rare. So there's plenty of opportunity to do this type of thing. Network/graph theory is one relatively recent example in ecology, and the application is still relatively rudimentary.

Fifth, related to the previous, I recently was involved with applying absorbing Markov chains to predicting the dispersal and mortality of wildlife populations across landscapes. This process involved interdepartmental collaboration with mathematicians/engineers to develop the relevant theory.

If I've piqued your interest, just start looking into different fields, the theories they operate under, and the math underpinning those theories. I can't speak for other fields, but in ecology I can point you to quantitative ecology and theoretical ecology. That's just a starting point, because math is ultimately relevant to all aspects of ecology. In my case, I'm interested in theoretical population genetics in ecology, which is also very math heavy.

If you find something that interests you, then consider finding university researchers that do related work and try digging into what they do specifically. Contact them to discuss their work and how someone with your type of background could potentially become involved in their field. Some might not respond, but others will be very supportive. Ultimately, your success down this path will depend less on your formal education and more on how you pitch the skill and background you have, as well as your ability to show initiative.

Answer 12

You should be somewhere in your early 30s, that's not too late. Go to programming: you can learn the basic skills online (leetcode is a great place, for example) in about a year or so, then join an open source project of your choosing for about a year or so as well - to show that you can apply those skills. That, plus your math creds should give you a resume that's good enough for an entry level job. The reason what you are studying is not sticking is because you are not applying your skills - the "use them or lose them" adage. Switching to programming will let you learn for real if you combine the theory you read with the practice. I was kind of in your shoes, but I was able to pull myself together and start a good programming career. If you are interested, I can post specific tips in comments.

Answer 13

Your story sounds reasonably similar to mine a few years ago. I somehow got a maths degree, but neither with good grades nor with some really deep and relevant kmowledge. Got problems finding a job because a job requires work experience and work experience requires a job.

I actually found a programming job in the end, one year after graduation. What helped me?

• it was an SQL job and many programmers do not like SQL
• Apparently studying maths tought me to look out for traps and special cases. The company sent me a small test project with some easy-to-spot corner cases, which they said the majority of applicants had ignored

What might have helped me even more?

• Have someone with relevant (recruiting) experience have a look at my cv and documents
• Have trained how to read other people's code
• Have better knowledge of somewhat peripheral aspects such as version control, unit tests, continous integration systems etc. This is nothing one cannot learn on the job, but if HR is just ticking a list, these things may be helpful
• Be slightly more explicit about the humble and down-to-earth odd jobs taken previously. I.E not "odd jobs", but "odd jobs (production line, construction, restaurants etc)"

I think it may also help if you get some understanding just how much above average your maths skills are. In programming, there will eventually be some point where calculations are necessary. I have had coworkers who regularly struggled with linear interpolation (a.k.a. rule of three):or who could not grasp how 0.1 + 0.1 + 0.1 could possibly be not exactly the same as 0.3 when calculated on a computer. Having a math guy in the team really can be an asset even if the maths does not go much beyond what can be learnt at high school.

Answer 14

I graduated with a Computer Science degree in 2016 with low grades. It took me 6 months to get my first job as a junior dev. The advice I can give you for getting a development role is that you create a website and put your CV there(like a portfolio/bio). These days if you show in the first 5 minutes of the interview that you have a website live that will immediately put you above the average person.

Answer 15

I don't have enough reputation to comment so I just add an answer here.

Since you insist on learning instead of just getting a job, instead of asking what do I learn, perhaps you should ask how do I learn, given that you have already recongized you didn't learn efficiently during your master degree.

If there's a university where you live, you could try sitting at classes there and talk to students and faculties. The point is that if you are not good at learning this stuff you need to talk to the others. In your situation only working on books on your own is not that helpful.