Live data from Hacker News

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

news.ycombinator.com

11–20 of 148 posts

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

#11
Most definitely not. It’s just that the focus is perhaps more on domain expertise and the production-side of things these days, rather than manually putting Tensorflow models together, which might give the impression that every problem has already been “solved”.

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

#13

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?

I think the difference now is that even a small company can aggregate data from all over the world which makes it more valuable- therefore a good data scientist/ engineer can be paid more than just ‘middle class’

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

#14
About the best time to ‘invest’ in anything that’s close-to-certain of yielding results: “The best time to plant a tree was twenty years ago. The second best time is now.” – Chinese proverb

Advanced data analysis / machine learning isn’t dated or old-fashioned at all, and I guess will continue to stay (or: become even more) relevant at least another decade. Not all ships haven’t left the harbor.

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

#16
I wonder with schools producing CS graduates at such high rates, how people want to distinguish themselves and find jobs?

The market seems to be flooded with students with CS skills. Actually, people from all fields — mechanical engineering, computational biology, EE, math etc — are entering data science. It is worrisome.

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

#17
Have you explored opportunities to apply data science to agriculture?

I'm interested in this space; I do some work with agricultural data acquisition hardware and software (e.g., soil moisture, environmental conditions, sap flow, plant/fruit growth monitoring), irrigation, fertiliser application) and I'm interested in ways this data could be used in predictive models, but I'm not at the stage of being able to focus on that aspect yet (still getting the core data logging/display tech working well, though we’re nearly there).

Feel free to get in touch (email in profile) if you'd like to connect and discuss.

To address your question, I think the world is still mostly at a very basic stage in its use of data analysis and statistics. Most of the talented people are employed on big salaries by a relatively small number large companies with huge budgets for specific applications (e.g., ad targeting, risk assessment, algorithmic trading).

But outside of that, not much is happening, so I think there are big opportunities to apply data science in new fields and make the benefits more widely distributed.

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

#19
post #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.…

I dont think I've been to two companies that had the same or even similar definition of 'data science'. Often it meant something like: see if you can use Tableau to produce new insights.

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

#20
post #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.

I work as a data scientist and every statement in your post sounds incorrect to me. SQL is useful but it's far from the most important tool. It's certainly unlikely to land you a job. It definitely won't solve 97% of problems. You either have a very skewed perspective of what data science is or you spend a lot of time on linkedin/medium where bad advice like this is parroted a lot.

Think about this - there are a bunch of other software developers who know SQL very well. If your advice was true, then every backend developer would be able to immediately land a data science job and do great at it without having to learn a bunch of math, ML-specific stuff and a whole other tech stack.

Post reply on HN