Live data from Hacker News

Mathematicians becoming data scientists

quomodocumque.wordpress.com

51–60 of 122 posts

Re: Mathematicians becoming data scientists

#51

Slightly off topic: They still can't build proper software. Academics (including mathematicians) are notoriously bad at writhing production grade software. This leads to handovers of 'proof of concepts' to seasoned software developer team who than struggle with the (often complex) mathematics/science behind it. Imho universities should give a bit more attention on how to write quality software; a bit of test driven d…

Ive been involved in projects where this was an issue. The main problem was that operations were not abstracted away from the types or boilerplate.

Re: Mathematicians becoming data scientists

#52
post #43

Earlier quoted context omitted.

I'm a data scientist with a stats background. I'm also a self-taught programmer (going on 15 yrs of programming in various languages). There are very few data science jobs that I am aware of where somebody will hand you a tidy data set and ask you to start creating models. For those jobs, it's great to go straight from stats/math to data science, as long as you learn a bit of R and some SAS along the way. Most data s…

Thank you! As mentioned separately, I suggested a data science boot camp after getting the Stats BS, work a couple of years as a data scientist, then go back for the MBA. My thinking RE the MBA was to give a sense of the business value of the analyses she's performing, and, to make it easier to promote her to executive positions. Maybe that's old school thinking, I know that the MBA in general gets a mixed reception…

To me, an MBA is more about business strategy. Knowing the relevance of data to the operations of a business is vital to being an effective data scientist. Knowing when to make the call to lay off 500 people is the job of somebody with an MBA. Data scientists prepare and present the evidence in the language of business. There is crossover, of course.

What many data scientists (myself included) find is that they often are excluded from meetings and conversations that provide the context for the analysis they are doing. I always tell my supervisors that it is very helpful for me to sit in on as many business strategy meetings as possible, just to listen, because it builds context around the work that I do and helps keep me properly focused.

On the flip side, many involved in business strategy do not understand the nuances of analysis performed to support their business questions. There can be many reasons for that, from not being directly involved in the analysis to being excluded from data science meetings. Effective business analysis and data science requires trust between the players and that trust is built through showing an ability to deliver focused, relevant, and accurate results that support decision making.

As somebody who likes to write code and dislikes sitting in tons of meetings, I tend to avoid climbing the career ladder to management positions. I'm happy in a Senior Data Scientist position. At my last job, I was being groomed for management and I never got to do any actual data science work. It was boring as hell. I made a lateral move to a different company so that I could be more hands on and work in an industry that is more fun. Now, I get to write code and build and run models every day. I also get to present the results and have a trusting relationship with the managers.

As your daughter finishes school and gets some job experience, don't be too quick to suggest routes leading to business strategy and management. While it's the "top of the career ladder" at many companies, so to speak, it's not for everybody.

Re: Mathematicians becoming data scientists

#53

Slightly off topic: They still can't build proper software. Academics (including mathematicians) are notoriously bad at writhing production grade software. This leads to handovers of 'proof of concepts' to seasoned software developer team who than struggle with the (often complex) mathematics/science behind it. Imho universities should give a bit more attention on how to write quality software; a bit of test driven d…

As a developer, I assure you that even some developers can't write production quality software. Especially some enterprise developers. They either over engineer and never ship or under engineer and ship crap.

Re: Mathematicians becoming data scientists

#54
post #13

I've been encouraging my daughter, a statistics major, to pursue data science by including Python/R in her studies and then possibly heading back for an MBA. But not sure if an MBA would be a benefit. Thoughts from actual data scientists?

Personally I think a PhD would be better than an MBA if she really wants to do data science, but generally speaking I'm for as more edu as possible, and I'm sure she'll benefit from an MBA too.

Lol, no. Just learn programming and start working for a company. No better way to learn data science than to work as a data scientist.

Re: Mathematicians becoming data scientists

#55

I've been encouraging my daughter, a statistics major, to pursue data science by including Python/R in her studies and then possibly heading back for an MBA. But not sure if an MBA would be a benefit. Thoughts from actual data scientists?

I've worked with dozens of data scientists and only one had an MBA. He didn't think it helped him get or do his job, and considered it a poor investment.

MS's and PhD's in stats, applied math, physics, computational bio/chem were far more common.

Re: Mathematicians becoming data scientists

#56
post #13

Earlier quoted context omitted.

Personally I think a PhD would be better than an MBA if she really wants to do data science, but generally speaking I'm for as more edu as possible, and I'm sure she'll benefit from an MBA too.

The PhD will only be useful in a small (but growing) subset of data science jobs. Their are data scientists who develop new algorithms and techniques, and those who apply the. For application, the PhD is probably overkill and extensive experience with a bachelor's, or a master's is better. For theory the PhD can't be beat, of course. I say the opportunity costs are high, and should be carefully weighed, because I hav…

It may not necessarily be the best option for the OP's daughter, but it is possible to do a PhD that uses data science as a tool rather than the focus. There's a lot of interesting work going on in academia using data science in a variety of fields (like medicine) related to predictive analytics (predicting hospital readmission, predicting therapy outcomes), time series analysis (analyzing EKGs, and other vital sign data) etc. A masters would likely allow you to work on similar projects, but if the goal is a PhD, there are certainly application rather than theory focused research groups across the country

Re: Mathematicians becoming data scientists

#57

What about the other way around? I'm from an engineering background, going in the direction of data scientist. Sometimes I find that my math skills could be stronger, and I try to read up on things when I encounter them, but still it sometimes feels like there is an infinite amount to learn. Maybe I could use some more systematic approach to it. Anyone else who has walked this path, and could come with some useful ad…

Stats and linear algebra are what you want...

On the linear algebra front, you get some understanding from your first course, but the more you internalize it by meeting the ideas in different contexts, the more useful it will be. A decent amount of higher math is turning things into almost-linear problems, and then trying to sort out the parts which don't quite fit...

Re: Mathematicians becoming data scientists

#58
One side of this that bugs the crap out of me: I have a PhD in math and, after getting sick of teaching mediocre students with a palpable aversion to mathematics, I spent a couple of years applying for data science jobs and getting very few responses. The few interviews I got seemed to go well, but I had no offers and gave up on leaving academics. I have experience in software development (C++), I have a portfolio of statistics/data analysis projects in R/RStudio, but what I think is toxic is having spent so many years in academics; I finished my Phd in 2003. Being an over-40 academic feels like an insurmountable liability, even though I have many of the skills that people complain about being in short supply. And another thing: get off my lawn, you rowdy kids! :|

Re: Mathematicians becoming data scientists

#59
post #21

I had two blog posts exactly on that topic, math/phys -> data science: - why: http://p.migdal.pl/2015/12/14/sci-to-data-sci.html (on academia vs industry) - how: http://p.migdal.pl/2016/03/15/data-science-intro-for-math-ph... (also got reprinted at KDnuggets)

Thanks for sharing this. Especially for someone who's thinking about getting a data scientist job.

Re: Mathematicians becoming data scientists

#60

One side of this that bugs the crap out of me: I have a PhD in math and, after getting sick of teaching mediocre students with a palpable aversion to mathematics, I spent a couple of years applying for data science jobs and getting very few responses. The few interviews I got seemed to go well, but I had no offers and gave up on leaving academics. I have experience in software development (C++), I have a portfolio of…

[deleted]
Post reply on HN