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Challenge: find work within 3 months (NYC based, no work authorization needed).

Conditions: Need one week-day off a week that I can make up with remote commitment on the weekend. Reason: I'm a Math PhD freshman, need the job but don't want to quit studies.

Question: If this were your life, what steps would you follow to achieve the goal of employment in 3 months given the following qualifications/experience?

1) Master's in math, undergrad in math, 3.9 and 3.6 GPA's respectively.

2) 2 years of work experience with MySQL and Python, but not really developing, mostly research on a Jupyter notebook that lead to a publication in mathematical biology. I'm decent with Python, have coded up some research papers in computer vision for practice, but I don't have the developer experience (unit testing, scripting, deploying, all jargon to me, I can just code algorithms but lack the developing skills around that).

3) I have varying levels of familiarity with (meaning I understand the syntax and to some extent can produce code): PySpark, MongoDB, Git, Unix/Linux, Bash, HTML, CSS, Javascript, Wolfram Mathematica, OCaml

4) I am currently (last month) working on an internship (more like a bootcamp since they just teach things to interns, don't assign any tasks) for Fullstack development, but it's mostly Front-End, but I think it's better than nothing on the resume and they have some Back-End workshops for stuff like MongoDB.

5) I have 3+ years experience lecturing undergraduate and graduate level mathematics/statistics at senior colleges. Anything from Stat to Calc to Linear and Modern Algebra to Numerical Analysis and programming labs in Mathematica.

Additional information: I've been accepted to a decent data science bootcamp, but it's 17.5k for 3 months (which I will have to borrow with at least 10% interest) and afterwards I am concerned the companies won't hire me if I need at least one day remote. That 17k is a big risk, so I'm hoping there are alternatives.

A potential approach:

Do many Kaggle competitions, put them on github, the math and technical knowledge is almost there for an entry-level position, maybe I need to showcase some work.

Another, more fantastic, suggestion: follow the PluralSight course on AWS Developer certificate and try to get it, that seems to make people employable.

Or, continue consuming PluralSight courses at a frenetic pace and putting more words on my resume... doesn't seem wise.

closed as off-topic by Dukeling, gnat, Dan Pichelman, jcmack, Joe Feb 16 at 0:02

This question appears to be off-topic. The users who voted to close gave this specific reason:

  • "Questions asking for advice on a specific choice, such as what job to take or what skills to learn, are difficult to answer objectively and are rarely useful for anyone else. Instead of asking which decision to make, try asking how to make the decision, or for more specific details about one element of the decision. (More information)" – Dukeling, gnat, Dan Pichelman, jcmack, Joe
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  • You state you want to find a job... but... what kind of job? On what industry? what role and responsibilities you seek? Please clarify and narrow it down so we can help you better. – DarkCygnus Feb 15 at 22:00
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    Is there some reason you don't have a research or teaching assistantship with your program? Items 1) and 2) would seem to make you well qualified for a such a position. Frankly 2), 3), and 4) are pretty weak tea except for very low level IT and development positions. There is going to be a lot of competition for those positions and they are going to be put off by your being in a Ph.D. program since you'd be unlikely to stick around long enough to pay back the effort of training you. Attending the data science boot camp while working on math Ph.D. seems like you are scattering your efforts. – Charles E. Grant Feb 15 at 22:01
  • @DarkCygnus Thanks I'll try to narrow it down in the question. Off the top of my head I would say Data Science, but I've noticed that means anything to anyone, for me it means statistics + "as many technical skills handling and manipulating large datasets as possible". That's why I've tried to gain some actual developing skills, thinking that Data Science is a bit of a wishy-washy term and people actually get hired to develop and deploy code while knowing some statistics and can think mathematically. – Mike Feb 15 at 22:20
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    Doing a PhD that normally takes 5-6 years of (more than) full time effort in one day a week seems rather problematic. Doing that while trying to gain a bunch of mostly unrelated data science/ professional programming skills seems suicidal. If the problem is that the university doesn't provide enough funding to live on in NYC and you don't want to take on loans for living expenses, it would seem to make sense to find a PhD program in a lower cost location that you can attend without spending 80% of your time on an unrelated job. – Justin Cave Feb 15 at 22:43
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    @Mike There are very few people who are up for a few hours of studying after getting home after a full day of work, not to mention doing this every day. – Dukeling Feb 15 at 23:16
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If this were your life, what steps would you follow to achieve the goal of employment in 3 months given the following qualifications/experience?

Step 0: Decide what kind of job you want, and in what industry. That will help you narrow down your search from the many kinds of jobs and industries out there.

Step 1: Once you know the job you want, search for potential companies that host those kinds of jobs. This you can search with help of things like LinkedIn, Google, your local Newspaper, friends and colleagues, etc..

Step 2: For each company you see and like, find out if they are currently hiring or if they have any openings. Then, tailor your base CV for that role, including and highlighting relevant information for it, and proceed to send it

Step 3: Repeat steps 1 and 2 until you get an interview. Take the interview and see how it goes. This would be the time to ask/negotiate the day off and anything else you need for your PhD studies. If everything is ok and you get an offer proceed to accept it if it's of your liking.

  • There should probably also be a step to do interview preparation, and lots of it (which should probably be done in parallel to the other steps, rather than before or after any one of them). You can be the most suitable candidate ever to actually do the job and still fail the interview miserably. You should do general non-technical interview preparation, company-specific preparation as well as broader technical preparation to make sure you actually have / gain the skills required to get and work in the type of job you want (i.e. skills every company hiring for that role will want). – Dukeling Feb 15 at 22:32
  • The steps are quite summarized, though. But yes, preparing for interviews is valuable. One good part of preparing for such interview is covered in step 2, when one is investigating the company one will apply to (the insights gathered greatly help to know a bit of what to expect from a possible interview with them). – DarkCygnus Feb 15 at 22:38
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From your comments I understand that you do have an assistantship that pays in the neighborhood of $25k/year. I can appreciate that $25k is next to impossible to live on in NYC, but unless you can go without sleep for months at a time, a full time data science job, a half-time assistantship, a Ph.D. program, and a data science boot camp would be far too much for most folks to handle. You're in grave danger at doing a crappy job at all of them. Very few entry level jobs are going to want to take on somebody who has so much on their plate.

Since your program doesn't allow taking a leave of absence, you'll need to find a job that pays better than your assistantship or take out loans. I'd strongly suggest discussing this situation with your advisor. Talk with your fellow Ph.D. students to see how they manage. If you are really committed to your Ph.D. program then it would make more sense apply the loan to your Ph.D. expenses rather than the data science boot camp. Part time data science jobs are rare. Doing a Ph.D. while working full-time is possible, but hard.

The biggest problem you face in your job search is that the job market is competitive, even in data science. Your math background is certainly strong enough, but your programming background is weak. You don't seem to have written any substantial, stand alone, computer programs. You also don't seem to have any experience working on a development team on a large project. You are going to be competing with comp sci./math/physics/econ majors and non-college grads who do have that experience. That puts you at a disadvantage for straight-out development jobs.

In your capsule description of your experience you seemed to list every technology you've ever used in an assignment. Don't do that. Tailor your skill list to the job you are applying for. Very few employers are going to care that you can write "Hello world" in OCaml. Most would regard that as pointless resume padding, and move on to the next candidate. You should be prepared to answer questions about any technology you list on a resume. If the interviewer could plumb the depths of your knowledge in a technology in just a minute of questioning, then it's not worth putting on your resume.

To pursue development jobs, I'd say your best bet is to develop some depth in a couple of mainstream technologies. Python and MySql are fine for this. Focus on writing stand-alone programs rather than experimental notebooks. While you are looking for work you might try contributing to an Open Source project that interests you. That would at least give you experience in development team workflows. Learn Git, and learn a testing framework. They won't seem very useful for your small hobby projects, but they're ubiquitous in development teams.

Your mathematical sophistication may make you a better candidate for analyst jobs. That's particularly true if you have a good background in statistics. In my experience, folks are way more likely to screw up a statistical analysis than to misapply SVD. Unfortunately, I suspect there are many more coding jobs than there are analyst jobs. You should tap into your mathematical mentor network to find them. The good news is that those jobs are probably more common in NYC then almost anywhere else in the world.

  • Thank you for your answer. Unfortunately, leave of absence is not allowed at this program, but taking a school loan is something to consider. I am curious about what programming background is considered strong. Mine is undoubtedly weak, but I believe I can improve on it quickly. By weak, do you mean I lack specific languages/methodologies? For example, do I need to be versatile in AWS services, Hadoop and Spark and NoSQL databases (i.e. know them enough to pass an interview) or is it weak in terms of experience, and nothing other than experience can remedy that in the eyes of an employer? – Mike Feb 15 at 23:14
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    @Mike - It's weak in terms of experience. Now, you can certainly get the equivalent of a few years of experience in less than a few years but that would most commonly happen by, say, working somewhere and delivering a bunch of large projects there not by doing boot camps or Pluralsight training. Employers would much rather have someone that can talk about how they used Hadoop to solve a real business problem than someone that's done enough training to answer some trivia questions without having ever used it in a real business environment. – Justin Cave Feb 15 at 23:22

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