It's a longer story, with summary is in "My story" from http://p.migdal.pl/2016/03/15/data-science-intro-for-math-ph.... Since it had some turbulent nature, it was hard for me to put it into a coherent narrative. And it may be even harder to put it in a way that is beneficial for others (involves my particular situation, skillset, network of contacts, personality).
If you mail me (my website's footer), I will send you a quick&dirty summary of my path & projects. In any case, some answers:
> Do you do blind calls?
Never! But if there is an opening for a full-time position sometimes I mailed them anyway, if they are interested in some specialised contracts; sometimes they were.
> Do you use a freelancing site?
No. I followed a mailing list with freelance projects in data viz. (By far the easiest place to start, as they can SEE my previous projects and current progress.)
> Do you work remotely?
Almost entirely. But for the last few weeks I am a bit more related to a particular company, and then I prefer to be on site (easier to talk etc).
> What is the typical contract, how much do you bill?
Since it varies a lot (and I want to increase it a bit), I am not comfortable to put in publicly. Expect for things I do it is also dependent on place in which I live, particular projects, negotiation skills, project uncertainty (data science is not webdev - each project has a research part).
> Does one have to do public talks to get recognised?
Yes. I mean, maybe it is not strictly necessary, but public talks (meetups, conferences, etc) and other public activity (blog posts, running communities) helped me a lot! (But I love it anyway.)
> How much do clients value your having a PhD?
A wonderful discussion starter, never a deal-maker.
> How do you animate the networking?
(Answered above.)
> Do clients find you, or do you find them?
In the last year (or more) it's only clients who contact me, and I accept (/follow up) or decline projects.
> Why are they buying, FOMO on a marketing dataset, or just plain curiosity on the subject?
?
> If you had to specialise in one niche market, what would be, what would be your approach?
If you were an animal, which... ;)
> Basically: what would be the steps you would take should you start only with the data science technical knowledge?
If you mail me (my website's footer), I will send you a quick&dirty summary of my path & projects. In any case, some answers:
> Do you do blind calls?
Never! But if there is an opening for a full-time position sometimes I mailed them anyway, if they are interested in some specialised contracts; sometimes they were.
> Do you use a freelancing site?
No. I followed a mailing list with freelance projects in data viz. (By far the easiest place to start, as they can SEE my previous projects and current progress.)
> Do you work remotely?
Almost entirely. But for the last few weeks I am a bit more related to a particular company, and then I prefer to be on site (easier to talk etc).
> What is the typical contract, how much do you bill?
Since it varies a lot (and I want to increase it a bit), I am not comfortable to put in publicly. Expect for things I do it is also dependent on place in which I live, particular projects, negotiation skills, project uncertainty (data science is not webdev - each project has a research part).
> Does one have to do public talks to get recognised?
Yes. I mean, maybe it is not strictly necessary, but public talks (meetups, conferences, etc) and other public activity (blog posts, running communities) helped me a lot! (But I love it anyway.)
> How much do clients value your having a PhD?
A wonderful discussion starter, never a deal-maker.
> How do you animate the networking?
(Answered above.)
> Do clients find you, or do you find them?
In the last year (or more) it's only clients who contact me, and I accept (/follow up) or decline projects.
> Why are they buying, FOMO on a marketing dataset, or just plain curiosity on the subject?
?
> If you had to specialise in one niche market, what would be, what would be your approach?
If you were an animal, which... ;)
> Basically: what would be the steps you would take should you start only with the data science technical knowledge?
http://p.migdal.pl/2016/03/15/data-science-intro-for-math-ph...