Find something you want to do, then find some big government or enterprise who wants to move away from Cognos or Crystal Reports to something sexy and pay for it by doing that.
one huge prob w/ running it from the cloud is that you will always be picked off by the Virtus of the world with their own hardware, saddled up in the same rack as the OMS running the exchange.
I'm founder of https://bitbank.nz cryptocurrency ai price prediction stats dashboard, API and bulk data service you can get to work lots with open source devs if you work lots on a specific niche and provide a good api
Write a book→ assert you are an expert due to existence of book→ hope people believe you→ charge to tell people things they already know but wanted to hear from an expert.
John D Cook's business is doing well, providing services on what is essentially data science, or most aptly put, "very applied mathematics"
https://www.johndcook.com/blog/services-2/
But he also has a reputation that has been built up over years through insightful blog posts. Many people in the applied math community know his writings, and there is a general recognition of his expertise.
https://www.johndcook.com/blog/
Data science is too general and faddish (I say this as someone whose job title contains that phrase). The market is saturated with too many people who claim they do data science. If someone were to give me their business card and tell me they did general data science work, I probably wouldn't even give them a second look.
My suggestion is to establish yourself in a few problem domains (e.g. data science for agriculture, data science for transportation, etc.) and show tangible results. I think that would improve your marketability.
I grew up around consultants, and as with any kind of consulting business, the advice that was given to me was to work for at least 3 different established companies in your domain of interest for 3 years at a time before setting up an independent consulting shop. Without that, you won't have a sufficient street cred to sustain a stream of business to keep you afloat. (that said, this advice is 15 years old -- the part about 3 years + 3 companies might not be applicable anymore, but I believe the part about building a reputation continues to be true).
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12 comments
[ 5.3 ms ] story [ 66.3 ms ] threadConceptually it isn't that hard.
Putting it in practice is not always easy.
I imagine a data science business would be a services business that you can sell to C-level executives.
But he also has a reputation that has been built up over years through insightful blog posts. Many people in the applied math community know his writings, and there is a general recognition of his expertise. https://www.johndcook.com/blog/
Data science is too general and faddish (I say this as someone whose job title contains that phrase). The market is saturated with too many people who claim they do data science. If someone were to give me their business card and tell me they did general data science work, I probably wouldn't even give them a second look.
My suggestion is to establish yourself in a few problem domains (e.g. data science for agriculture, data science for transportation, etc.) and show tangible results. I think that would improve your marketability.
I grew up around consultants, and as with any kind of consulting business, the advice that was given to me was to work for at least 3 different established companies in your domain of interest for 3 years at a time before setting up an independent consulting shop. Without that, you won't have a sufficient street cred to sustain a stream of business to keep you afloat. (that said, this advice is 15 years old -- the part about 3 years + 3 companies might not be applicable anymore, but I believe the part about building a reputation continues to be true).