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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?

#131

Post by disgruntledphd2 »

beckingz wrote: post #129
disgruntledphd2 wrote: post #50

Earlier quoted context omitted.

This is a deeply misleading (though somewhat accurate) comment. The reason it's misleading is because the 70% above (who may be called data scientists) are not actually data scientists, at best they are data analysts. In general, the core difference between data scientists and data analysts is that the former can code in at least one language (SQL doesn't count, unfortunately). However, because the term data science…

Didn't facebook start this by calling their Data Analysts Data Scientists?

No, it was a different role. The original data scientists were people who could both run large scale social science experiments and write mao reduce jobs to analyse them.

Unfortunately, it was such a great name that everyone stole it, and they eventually had to call all of their analytics people data scientists (as otherwise they couldn't hire).

I remember being very angry when they changed all the product analytics people to be data scientists as many of them (the ones I knew, at least) we're strictly SQL monkeys.

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

#132

Post by ghaff »

d0mine wrote: post #107
ghaff wrote: post #68

Earlier quoted context omitted.

In general, domain knowledge is incredibly valuable and will generally trump someone who may have some more technical skills but doesn't know the field. I'd add that a lot of larger companies--heard someone from Shell talking about this a couple months ago--are training up people who have knowledge of the business with "citizen data scientist" skill sets. Without knowing all the details of your situation, it seems at…

There is a book "Range: Why Generalists Triumph in a Specialized World" which claims there are domain-specific problems that are more likely to be solved by people originally outside that domain.

I don't doubt there are examples where a fresh set of eyes and lack of knowledge about what can and can't be done can break out from "the way we've always done things." But it's probably not the way to bet in the general case.

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

#133

Post by dumb1224 »

CinchWrench wrote: post #96
st1x7 wrote: post #24

I work as a data scientist and have some perspective on this. There's no boat to miss, you'll probably be fine. Just keep a couple of things in mind - The fundamental skills that you need are mathematics and software engineering. Depending on your background it might take years of additional studying. - There is a big oversupply of people for the junior-mid level data science jobs. There are more people who want to g…

>the fundamental skills that you need are mathematics and software engineering So much this. If I have to interview another junior-level DS who has a MNIST project in their github and still somehow can't manage fizzbuzz or a fibonacci function I'm probably going to take up religious asceticism. EDIT: I said junior, but I meant Senior. We're talking people with PhD's who claim to have done extensive software engineeri…

I think there is an issue with focus of the role. If job is more focused on programming then the candidate must be at least proficient in coding. Otherwise if you need a mathematical modelling person then you need to look into relevant training background (undergrad degree etc). A lot of my colleagues in my research institute are from a physics background. Because molecular biology require a lot of statistics. They are ok coders but what they really contribute is the modelling part.

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

#134

Post by ethbr0 »

NoOneNew wrote: post #94
ethbr0 wrote: post #83

Earlier quoted context omitted.

Have you collected data from and deployed products to a 2000+ store environment?

Okay, how is my argument changed if I answer yes or no? Is what you're talking about a data sci's responsibility or not? If collecting, analyzing and deploying data in reports or db is too difficult for you, data sci isn't for you. I'm not telling them HOW to do their job. I'm clarifying that you have to DO the job if you signed up for it. Dont like it? Get out. We all screwed up by taking jobs we didnt like. Nothing…

I'm curious about the relative experience you're talking from.

You're trying to make a point about the fact that you need to push the business and/or obtain data yourself, but I'm saying that can be a vastly more difficult problem than you think (or just flat impossible) at scale.

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

#135

Post by giardini »

thom wrote: post #123

Genuinely shocked by this question. There is no part of the data science stack that is in any way settled. Even more broadly I don’t think statistical best practice is at all established, or at least well distributed. You haven’t even missed the boat in terms of being able to make money off raw buzzwords and zero skills. At the very basic technical level, there’s infinite work to be done optimising machine learning s…

And hope that boat is not the Golgafrinchan Ark Fleet Ship B:

https://hitchhikers.fandom.com/wiki/Golgafrinchan_Ark_Fleet_...

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

#136

Post by giardini »

As others have noted, many data scientists work in Excel. This book, which teaches data science, does just that:

"Data Smart: Using Data Science to Transform Information into Insight" by by John W. Foreman

https://www.amazon.com/Data-Smart-Science-Transform-Informat...

This is likely the quickest way to start.

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

#137

Post by sethammons »

tomhoward wrote: post #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 o…

I just started getting interested in sensors and ranching/agg. Can you link me any resources? Curious on the right terminology, some players in the space, etc. any help pointing me in the right direction would be really appreciated!

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

#138

Post by pkalinowski »

ethbr0 wrote: post #134
NoOneNew wrote: post #94

Earlier quoted context omitted.

Okay, how is my argument changed if I answer yes or no? Is what you're talking about a data sci's responsibility or not? If collecting, analyzing and deploying data in reports or db is too difficult for you, data sci isn't for you. I'm not telling them HOW to do their job. I'm clarifying that you have to DO the job if you signed up for it. Dont like it? Get out. We all screwed up by taking jobs we didnt like. Nothing…

I'm curious about the relative experience you're talking from. You're trying to make a point about the fact that you need to push the business and/or obtain data yourself, but I'm saying that can be a vastly more difficult problem than you think (or just flat impossible) at scale.

Why single data scientist should be responsible for obtaining data from 2000 stores? Data at scale requires people at scale. Data engineers would do this job.

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

#139

Post by rmelhem »

TnkBldr wrote: post #59
bvcvbuiy wrote: 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.

Totally agree. I believe the set theory thinking one gains with SQL helps to deal with tables(databases) in any framework. SQL can become super tricky as well (depending on the context), say you want to get the list of users who are active for 'n' consecutive days from a dataset that has daily user activity for an year. It's not very difficult but needs some effort. However, for a data science beginner, SQL is the be…

"However, for a data science beginner, SQL is the best place to start."

I totally agree with that statement. Being a beginner myself in the DS field, I'm living through this right now in my job. And, as a plus, working with SQL everyday is also helping me a lot to have different perspectives in handling the Python/Pandas DataFrame.

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

#140

Post by j45 »

This might be shinging a light on something surprising -- After taking in a Data Science course at Microsoft last year..

Try to remember the very beginning of Data Science is often cleaning up data in Excel, and then learning to do it with excel functions.. and then learning to do the same in Python.

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