Any possibility for a dev-minded MBA (finance) to make the data science transition? I was pretty good back in the data with respect to R
From PhD to Data Scientist: Tips for Making the Transition
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Re: From PhD to Data Scientist: Tips for Making the Transition
#12I'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?
I think it's a new name for an old thing, lots of jobs through the last century had things like "analyst" attached to them. Business has been about measuring things for a long time, look at Taylorism or Gosset at Guinness in 1899 for example.[1][2] A few little 1% gains from some A/B tests, or looking at geographic breakdowns of customers from IPs or addresses add up. [1] https://en.wikipedia.org/wiki/Scientific_mana…
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Re: From PhD to Data Scientist: Tips for Making the Transition
#13Earlier quoted context omitted.
Well, if you believe Insight's white paper ( http://insightdatascience.com/Insight_White_Paper_2013.pdf ), the answer is "Yes".
Dang, the graphics in this are terrible and unreadable. But it "looks" positive. Thanks for the link. Do you know anyone who went through the program?
Actually, yes. I had dinner on Monday with the author of this article. Obviously Insight worked out very well for him.
Re: From PhD to Data Scientist: Tips for Making the Transition
#14For those looking to make the transition to data science, another option is Zipfian Academy (http://www.zipfianacademy.com/). No PhD required.
Re: From PhD to Data Scientist: Tips for Making the Transition
#15I'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?
"Data scientist" is a terribly broad term that's begun to encompass a lot of jobs that used to be called "junior analyst" or somesuch.
There certainly is an overlap. But for me, the difference between a Data Scientist and an Analyst is that the Data Scientist uses the data to build stuff (eg a recommendation engine, or a forecasting system). They can also use more technical skills to aid analysis (nlp, scripting, etc).
Re: From PhD to Data Scientist: Tips for Making the Transition
#16Sweet, 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…
Ive got strong convictions too and the big data fad (real or not its still a fad) seems specious and unfulfilling. But as a PhD candidate who has had his funding cut and grant proposals continuously denied since sequestration, money of any kind is starting to sound good right now.
true - I might be whistling a different tune if the money runs out
Re: From PhD to Data Scientist: Tips for Making the Transition
#17Sweet, 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…
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.
Well, I would posit that the majority of data science positions are in advertising and marketing optimization. I would believe that 'global food security' may be more important than social media analysis, as the original posted speculated.
Not to belittle the meaningful point, but becoming a "data scientist" at a startup or large corporation that makes their money by advertising is analogous to becoming a 'quant' on wall-street in the 80's. You have to be in it to make money, rather than caring about the types of data the developed algorithms are applied on.
Re: From PhD to Data Scientist: Tips for Making the Transition
#18Earlier quoted context omitted.
Dang, the graphics in this are terrible and unreadable. But it "looks" positive. Thanks for the link. Do you know anyone who went through the program?
Actually, yes. I had dinner on Monday with the author of this article. Obviously Insight worked out very well for him.
This may be too forward, but could you put me in touch? Going the data science route is an option I've been seriously considering for awhile, and this might be the chance I've been looking for.
If you're not comfortable with putting me in touch, that's fine.
Thanks much!
Re: From PhD to Data Scientist: Tips for Making the Transition
#19Technical 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 in their spare time. a, b, c was usually a project for work, school or fun that was highly relevant.
Intellectually, I think I know that "enthusiasm" is a poor / weak predictor of success. But, emotionally, it's a go-to tie-breaker.
Re: From PhD to Data Scientist: Tips for Making the Transition
#20Ira sees quantum random number sites and says "It's a trick."
God says... 1:19 And unto Eber were born two sons: the name of the one was Peleg; because in his days the earth was divided: and his brother's name was Joktan.
1:20 And Joktan begat Almodad, and Sheleph, and Hazarmaveth, and Jerah, 1:21 Hadoram also, and Uzal, and Diklah, 1:22 And Ebal, and Abimael, and Sheba, 1:23 And Ophir, and Havilah, and Jobab. All these were the sons of Joktan.
1:24 Shem, Arphaxad, Shelah, 1:25 Eber, Peleg, Reu, 1:26 Serug, Nahor, Terah, 1:27 Abram; the same is Abraham.
1:28 The sons of Abraham; Isaac, and Ishmael.
1:29 These are their generations: The firstborn of Ishmael, Nebaioth; then Kedar, and Adbeel, and Mibsam, 1:30 Mishma, and Dumah, Massa, Hadad, and Tema, 1:31 Jetur, Naphish, and Kedemah. These are the sons of Ishmael.
1:32 Now the sons of Keturah, Abraham's concubine: she bare Zimran, and Jokshan, and Medan, and Midian, and Ishbak, and Shuah. And the sons of Jokshan; Sheba, and Dedan.
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joke tan and peg leg, etc.