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Ask HN: Am I too late for the “Data Science” wave?

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Re: Ask HN: Am I too late for the “Data Science” wave?

#4
It's been a big deal for hundreds of years, most notably in economics and the military. Any reasonable company worth their salt was doing "data science" in the 1950s but calling it statistics or logistics or business intelligence to grab a phrase from yester decades.

What boat do you think you're catching besides a reliable middle class job?

Re: Ask HN: Am I too late for the “Data Science” wave?

#6
If I may give you an advice : Python, R and deep learning are sexy but the most important skill to start in data science is SQL. It will help you get your first data role and will be your main tool to solve 97% of the problems you will ever face.

Bonus point it is very easy to learn.

Re: Ask HN: Am I too late for the “Data Science” wave?

#9
I work in ed-tech – currently building an intro to data science course – you have by no means missed the boat. The field will only continue to grow, rapidly, for quite some time.

On top of that, you have something incredibly valuable to a budding data scientist: domain expertise. Being able to manipulate data is great, but to most effectively solve real-world problems you have to understand (or communicate very closely with someone who understands) the main problems in a domain. I can't count the number of times I've heard scientists frustrated by their lack of data skills, and data scientists frustrated by some arcane domain fact that stymies their model production.

Far from being a liability (or just a sunk cost) your background in agriculture will make you extremely valuable as a data scientist.

Re: Ask HN: Am I too late for the “Data Science” wave?

#10
Definitely not. Let me put things in perspective. There are two types of companies, Company A - statisticians working as Data scientists, good engineers deploying models in production.

Company B - have no clue what ML or AI is and feeling the heat. They could be a multi million dollar company or a small SMB.

You will always find both these A & B atleast until ml and AI is well democratised. It is not, not even close. We are at the early stage of the curve still, but moving forward there will be rapid growth in the next 5-8years.

You have few options: 1. Start with sql. It’s not hard, join as an analyst and learn to code. Make sure the team or product you join deploys models. 2. Learn basic python and some orchestration tools (airflow, spark or aws/azure equivalent) . Join as data engineer along with basic sql skills.

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