31–40 of 91 posts
For those looking to make the transition to data science, another option is Zipfian Academy ( http://www.zipfianacademy.com/ ). No PhD required.
If you want to pay money for experience, why not get an actual degree from an accredited institution?
A more realistic alternative to Insight is to do a (paid) internship at a tech company. This is the path I took.
Technical skills aside, the best piece of advice in the article is "show them that you want it." I've conducted countless interviews / hires where it basically went: candidates P & Q are the best on paper and in person, but candidate P said x, y, z or did a, b, c, and seems to really want this job and work in our company x, y, z was sometimes as simple as enthusiasm, and other times was in describing what he/she did…
Earlier quoted context omitted.
calling all data scientists - why not consider becoming a computational biologist? The pay is shit, you're at the whim of the funding moods of the day, and contrary to your last statement most of the results don't really ever go on to affect anyone.
I agree about the pay. It really sucks. But the other things depend what you work on and where. If it's cancer or food security, the funding is there and not going away. And you can choose how direct the outcomes are by choosing the position. I'm not saying everyone should do it, but if you're good enough to breeze into highly paid positions at top tech companies, you're good enough to get a really interesting positi…
I worked in a lab at HMS that sounded interesting on paper but wasn't all that interesting in practice. The researchers did the same stuff as you would at The Office, they checked ESPN.com, went to meetings, typed in some SQL and Perl codes for a while, went on coffee break, complain about something, go to another meeting, fart around with the design of their conference poster, etc ad nauseum. Then they all just went to go work at some big corporation, anyway. The upside was low expectations so I was able to work almost full time as a contractor on something interesting at the same time.
Earlier quoted context omitted.
You're everything that everyone hates in academia. Congratulations as I hear that self importance is one of the key ingredients to solving the biggest problems facing the world today.
I doubt that. Firstly because most people don't hate anything in academia, and secondly because you know very little about me. Perhaps my short comment sounded more arrogant than I am... I'm motivated by wanting to help people. If given the choice between trying to help alleviate starvation for little money and trying to optimise advertising on some website for a shitload of money, I'll take the former. Interesting t…
Definitely not. But the way one expresses them certainly is.
Technical skills aside, the best piece of advice in the article is "show them that you want it." I've conducted countless interviews / hires where it basically went: candidates P & Q are the best on paper and in person, but candidate P said x, y, z or did a, b, c, and seems to really want this job and work in our company x, y, z was sometimes as simple as enthusiasm, and other times was in describing what he/she did…
Should I start putting every substantial R/Python script I write, even if they are based on some tutorials, on the Github/Personal-Website? Is that how I "show"? I missed the Github bus for all my previous projects.
Sweet, according to his list I'm over-qualified. Interesting to think it would be so easy to make the transition to data science. Except I can't imagine wanting to work on less important problems than the ones I work on now. Global food security vs. social network analytics. Yeah, fuck the money. edit: calling all data scientists - why not consider becoming a computational biologist? We have hard problems, real outco…
Sweet, according to his list I'm over-qualified. Interesting to think it would be so easy to make the transition to data science. Except I can't imagine wanting to work on less important problems than the ones I work on now. Global food security vs. social network analytics. Yeah, fuck the money. edit: calling all data scientists - why not consider becoming a computational biologist? We have hard problems, real outco…
And in my opinion, as inexperienced as it might be compared to more established scientists, computational biologists are ready for biology, but biologists are not ready for computational biology.
Sweet, according to his list I'm over-qualified. Interesting to think it would be so easy to make the transition to data science. Except I can't imagine wanting to work on less important problems than the ones I work on now. Global food security vs. social network analytics. Yeah, fuck the money. edit: calling all data scientists - why not consider becoming a computational biologist? We have hard problems, real outco…
What skills do we need to learn to get into such a position? That is apart from statistics and programming? How much effort will go into learning that stuff?
- statistics, probability, and especially probabilistic inference
- nix/gnutools
- multiple scripting languages (Ruby, Python, Perl, BASH)
- at least one data-oriented language (R, Octave)
- understanding of molecular biology (read Molecular Biology of the Cell)
- applying machine learning tools to new problems
- understanding the major high throughput biological technologies and the kinds of data they produce, along with the current tools used for processing the data
You could pick up all of that in a year of intense self-study, and less assuming you already have some of those skills.
Technical skills aside, the best piece of advice in the article is "show them that you want it." I've conducted countless interviews / hires where it basically went: candidates P & Q are the best on paper and in person, but candidate P said x, y, z or did a, b, c, and seems to really want this job and work in our company x, y, z was sometimes as simple as enthusiasm, and other times was in describing what he/she did…
Should I start putting every substantial R/Python script I write, even if they are based on some tutorials, on the Github/Personal-Website? Is that how I "show"? I missed the Github bus for all my previous projects.
If you're going to go the coding route, put up a working page, publish a blog entry about it, publish a working app, etc.
The key is to show effort (I spent time on this) and relevancy (I'm solving a problem that you might care about).
Sweet, according to his list I'm over-qualified. Interesting to think it would be so easy to make the transition to data science. Except I can't imagine wanting to work on less important problems than the ones I work on now. Global food security vs. social network analytics. Yeah, fuck the money. edit: calling all data scientists - why not consider becoming a computational biologist? We have hard problems, real outco…
I am graduating phd bioinformatician, most likely going to transition into industry. It's very easy to be caught up with the self importance of academia because you are essentially in a bubble. It's great to be passionate about science, but I really dislike religifying academia. It's almost expected of aspiring academics to live like monks and just to be okay with shitty pay and long hours. That's bullshit and academ…
I can see this complaint in humanities academia, but pay in the sciences past the PhD student level is pretty reasonable. You could probably make more elsewhere, but it's not like you're scraping by on ramen noodles as a bioinformatics professor or anything. Postdocs typically make $50-60k, and professors start at something like $90k at the minimum, easily up to $120k, $150k, or more after tenure, especially if you're in a hot area like bioinformatics, have made a name for yourself, and can get a position at a top-30ish place. Unlike in tech, those salaries often come in places with a lower cost of living than SF, too (at least if you want them to). Six figures goes pretty far in Atlanta, Austin, Urbana-Champaign, Ames, or Raleigh, for example.
You could beat that in industry, but either way you're making solidly in the top 10% of U.S. salaries. And if you really need more money, most universities will let you do 20% consulting time, or do a spinoff startup. There are admittedly other reasons not to go into science academia (the list is pretty long, actually), but fear that you'll have to take a vow of poverty doesn't seem like a strong one.