Reading (or hearing) “I want to learn data science” is common. Followed by helpful comments and directions on how to do this and break into the profession. Somehow it makes sense. Both the ambition and the advice. But, does it make sense?

Consider similar questions “I want to learn mathematics” or “I want to learn consultancy”.

Most people would say that mathematics is a broad category and inquire about current knowledge. If the current knowledge is below a threshold perhaps some basic training can be recommended. Otherwise, it’s too broad and we have to dig deeper. Secondly, people would instantly ask “What for?”. What is the person actually trying to accomplish?1

Consultancy is a very broad profession and/or job title. You can consult on basically anything, and therefore it’s impossible to answer the question. Learning how to handle clients is…well tough to answer on paper. Doing it is probably the best solution.

Let’s return to data science. Somehow there is a plan. There are tutorials. There are success stories of breaking into the industry. Consider the amount of jobs that were relabeled as data scientist. Seriously, can we answer such a question?

No we cannot.

Typically, this is the spot where the writer offers their wisdom and an alternative. Sorry. Not today.

If you’re an aspiring data scientist I now officially welcome you in the company of all other professions where you have to make the plan, do the work and be a bit lucky.

Changing profession or careers is difficult, and the challenges are different for each person. All I can offer is to make small but steady improvements towards your goal.

  1. Funnily the road towards being an academic mathematician is simple. Executing this is hard (master, phd, tenure, …). ↩