From PhD to Data Scientist: Tips for Making the Transition • Hacker News Board

Re: From PhD to Data Scientist: Tips for Making the Transition

#41

Post by clearspandex » Wed, Jul 31, 2013, 11:52 PM UTC

shoyer wrote: post #31

flanger wrote: post #14

For those looking to make the transition to data science, another option is Zipfian Academy ( http://www.zipfianacademy.com/ ). No PhD required.

No PhD required, but you're expected to pay 14k in tuition. In contrast, Insight pays you. 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.

Often advanced degrees at universities are much more expensive (http://datascience.berkeley.edu/admissions/tuition-and-finan...) than an intensive program such as Zipfian and take much longer. I hope that private education institutions (such as GA, Hackbright, Dev Bootcamp, etc.) can coexist happily with traditional universities, as they each fill a different niche. Universities are in the business of training researchers and professors (and do a great job at that) while alternative educational companies aim to produce industry practitioners (similar to trade schools).

I highly recommend internships and they are wonderful if you can get one. Unfortunately not everyone can be so lucky, either due to lack of experience/technical abilities or an advanced degree (not everyone goes to college). I believe these alternative educational routes are democratizing such industries and many of them offer scholarships and tuition assistance programs.

Re: From PhD to Data Scientist: Tips for Making the Transition

#42

Post by dev1n » Wed, Jul 31, 2013, 11:55 PM UTC

Blahah wrote: post #4

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…

Maybe you could help me out here. I'm split on the whole data science in research vs business. I'm an undergrad Senior majoring in CS (minors in math and Computational Science). All the data science jobs I see for research firms require a PhD. I'd much rather work for a research firm than as an analyst for a business (I think). Any suggestions for someone looking to get some experience before pursuing more schooling? (not like I don't enjoy my classes but I'd rather not drop the dough after undergrad if I can get decent experience and a salary to help pay for a graduate program)

Re: From PhD to Data Scientist: Tips for Making the Transition

#43

Post by aet » Wed, Jul 31, 2013, 11:55 PM UTC

dudurocha wrote: post #27

gburt2 wrote: post #25

"Recursive programming"... as in, programming using recursion? Why would this be important to "data science"? Surely loops are just as effective.

Are you serious? How would you iterate over a set of rules and a big data volume, without using recursion?

A loop? Can you please explain?

Re: From PhD to Data Scientist: Tips for Making the Transition

#44

Post by Blahah » Wed, Jul 31, 2013, 11:56 PM UTC

daemonk wrote: post #37

Blahah wrote: post #4

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…

There is definitely an academic bubble. The infamous ivory tower. But in biology specifically, many of the problems are objectively important (as judged by society). And some people really do love spending all their waking hours working on them, and don't give a crap about the money.

I wouldn't call it virtuous, but it is deeply intellectually satisfying.

Agree about biologists not being ready - computational biology needs more computer scientists, not more biologists.

Re: From PhD to Data Scientist: Tips for Making the Transition

#45

Post by Blahah » Thu, Aug 01, 2013, 12:03 AM UTC

dev1n wrote: post #42

Blahah wrote: post #4

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…

Maybe you could help me out here. I'm split on the whole data science in research vs business. I'm an undergrad Senior majoring in CS (minors in math and Computational Science). All the data science jobs I see for research firms require a PhD. I'd much rather work for a research firm than as an analyst for a business (I think). Any suggestions for someone looking to get some experience before pursuing more schooling?…

Depending on where you are in the world, you could consider applying for computational jobs at some of the biotech giants (or startups, depending on your cultural preference). There are plenty on the US west coast and around Boston, Seattle, etc.

An alternative is to get a programming job doing something relevant (e.g. something with applied machine learning) and use those skills to work on open-source bio projects in your spare time. You'd then have some money, relevant experience, and demonstrated interest which could be a good foundation for graduate work if you decided to go that route, or for a career in data science if you don't.

Re: From PhD to Data Scientist: Tips for Making the Transition

#46

Post by daemonk » Thu, Aug 01, 2013, 12:09 AM UTC

Blahah wrote: post #44

daemonk wrote: post #37

Earlier quoted context omitted.

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…

There is definitely an academic bubble. The infamous ivory tower. But in biology specifically, many of the problems are objectively important (as judged by society). And some people really do love spending all their waking hours working on them, and don't give a crap about the money. I wouldn't call it virtuous, but it is deeply intellectually satisfying. Agree about biologists not being ready - computational biology…

Glad to see someone's enjoying it. I think I came out my program more jaded than the average student.

I agree that there are intellectually satisfying problems to solve. However, without getting into the tedious debate on the values of basic science vs translational science, how much of that intellectual satisfaction is mental masturbation?

Are these problems really that important? How much of the cool intellectual questions will directly give you a meaningful biological interpretation? Perhaps this is more of a comment on our field. I found a lot of the intellectual satisfying questions during my phd to involve algorithms/data structures, which mostly are just the tools to get at the biological interpretation.

Re: From PhD to Data Scientist: Tips for Making the Transition

#47

Post by scott_s » Thu, Aug 01, 2013, 12:10 AM UTC

_delirium wrote: post #40

daemonk wrote: post #37

Earlier quoted context omitted.

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…

> shitty pay 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, especi…

My biochem friend just accepted a post-doc at a respected lab for $39k.

Re: From PhD to Data Scientist: Tips for Making the Transition

#48

Post by aet » Thu, Aug 01, 2013, 12:10 AM UTC

tomrod wrote: post #2

I'm currently finishing a PhD in economics and have spent a lot of time learning the exact technologies he suggests (Python, SQL, a bit of R). Working as a data scientist would be an awesome opportunity. But are most companies _really_ in need of so many data scientists, or is it just a trend?

Have you already started into your specialty? Maybe you should do econometrics.

Re: From PhD to Data Scientist: Tips for Making the Transition

#49

Post by singingfish » Thu, Aug 01, 2013, 12:12 AM UTC

daemonk wrote: post #37

Blahah wrote: post #4

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 spent so long at uni they started paying me to stay - not quite got a PhD yet so I'm still kicking around the system, but unless you're very lucky uni is a pretty crappy place to work. A lot of what used to be good about working at uni has been stripped away by increasing class sizes, increasing bureaucracy and decrease in discretionary time.

A couple of years ago I got a long term freelance gig which I was describing to a professor I talk to about once a year the other day. He said:

"Interesting work, good money, and they leave you alone to get on with it. Sounds brilliant".

Although my current work has next to nothing to do with what I did at uni, it was a valuable experience. However I don't think most people are as lucky as me.

Re: From PhD to Data Scientist: Tips for Making the Transition

#50

Post by singingfish » Thu, Aug 01, 2013, 12:16 AM UTC

dev1n wrote: post #42

Blahah wrote: post #4

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…

Maybe you could help me out here. I'm split on the whole data science in research vs business. I'm an undergrad Senior majoring in CS (minors in math and Computational Science). All the data science jobs I see for research firms require a PhD. I'd much rather work for a research firm than as an analyst for a business (I think). Any suggestions for someone looking to get some experience before pursuing more schooling?…

Most jobs in high tech that push on the fronteirs of scientific knowledge that have a group leadership role need a PhD in charge of the team. Back when I worked in biotech, around 3/4 to 5/6ths of the team leaders had PhDs. I wouldn't expect this to have changed. For a commercially viable biotech company, salaries are pretty decent at that level.