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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?

#51

Post by deng »

jimbob45 wrote: post #29
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…

> There is a big oversupply of people for the junior-mid level data science jobs. Honest question is there any field where that isn’t true right now? Seems like there are no junior jobs in any sector.

German here. From my perspective it's hard to find

- embedded systems programmers, meaning people who know real-time systems, have good C/C++ knowledge, know their way around the Linux kernel and are also able to do basic things with a scope.

- good(!) C++ programmers in general

- people who know devops and software development infrastructure

C++ might not be sexy, but there's a vast amount of legacy software out there which is not going away anytime soon.

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

#52

Post by disgruntledphd2 »

cambalache wrote: post #42

1970- Hey Guys I want to start programming with the PDP-10.Did I miss the boat? 1980- Guys I want to learn about micro-controllers, is it too late? 1990- GUI programming 2000- Linux, Internet, you name it 2010 -. Javascript In 30 years time (at the very least) there will be still Data Science. So if you are really up to it, id does not matter if you should have started 5 years ago or now. If you suck at it or really…

But there's been Data Science jobs since at least the 50's.

50-60's: Operations Research 70's: Statistics 80's: KDD (knowledge discovery in databases) 90's: analytics (statistics again) 00's: Data science 10's: ML/AI 20's: ???

The tools and problems may have changed, but the core skills (statistics, some coding and data awareness) are identical.

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

#53

Post by disgruntledphd2 »

vector_spaces wrote: post #23
st1x7 wrote: post #20

Earlier quoted context omitted.

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 bunc…

A surprisingly vast contingent of software developers do not know SQL, let alone know it very well. And as others have mentioned in this thread, data science looks differently at different companies. For many, the math and "ML-specific stuff" ends up being a very small part of the process. For them, data quality and data cleaning take up the overwhelming majority of hours in a given project, and SQL chops will take y…

I think you're both right.

I find it hard to imagine successful data scientists who don't know SQL.

OTOH, I find it hard to imagine (even though I've met some) successful data scientists who only know SQL.

I suppose it's necessary but not sufficient.

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

#54

Post by 0x202020 »

brnt wrote: post #19
droaak wrote: 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.

Absolutely this. My side of the engineering department has taken a hard stance on what our definitions of Data Analyst, Data Engineer, Data Scientist, Machine Learning Engineer and Applied Scientist are. We have had a few issues with people wanting a different job title while interviewing and we supply them with our description plus a path from the position we believe they are to what they want to be. The ones who have taken these offers have been some of our best hires.

On the other hand the analytics/sales teams have many DS and MLEs, a DA is basically a “junior” for them, but they routinely have to reach over to an engineering team to do pretty basic SWE skills that they are supposed to cover themselves

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

#56

Post by birdsbirdsbirds »

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…

>There is a big oversupply of people for the junior-mid level data science jobs.

Which shouldn't be too much of a problem because they have the skills to analyse the market and find a local optimum that suits them.

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

#57

Post by jeffreygoesto »

deng wrote: post #51
jimbob45 wrote: post #29

Earlier quoted context omitted.

> There is a big oversupply of people for the junior-mid level data science jobs. Honest question is there any field where that isn’t true right now? Seems like there are no junior jobs in any sector.

German here. From my perspective it's hard to find - embedded systems programmers, meaning people who know real-time systems, have good C/C++ knowledge, know their way around the Linux kernel and are also able to do basic things with a scope. - good(!) C++ programmers in general - people who know devops and software development infrastructure C++ might not be sexy, but there's a vast amount of legacy software out the…

That is true. I found that for embedded C++ to be successful, you need to have some good (excellent sometimes was harmful, but that's a different topic) C++ _as well as_ good domain and optimization skills. It's a combination that is more and more scarce. C++ tends to be used in domains where size and speed matter. You need to know what the compiler and machine will do with your code to be fast. And what's more, only the domain knowledge will let you pick the right data structures to be fast and compact in the first place.

And there are a lot of foot guns around... ;-)

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

#58

Post by bvcvbuiy »

st1x7 wrote: post #20
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.

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 bunc…

My job title is data scientist even though you may not think of me as a 'true' data scientist. Just to give you some context I work in an ecommerce startup. Depending on your industry and the size of your company things may be very different.

I maintain one machine learning model that is very core to our business but doing 'machine learning' is a very portion of my job.

> 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.

In some companies Data scientists are very software development oriented but that is not the case of everywhere. Think about this : software developers who know SQL very well usually don't like cleaning data, they don't necessarily have good interpersonal skills required to solve business problems, they are not necessarily interested in solving business problems, and they may tend to think that more software is the solution to all problems.

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

#59

Post by TnkBldr »

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 best place to start.

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

#60

Post by wallscratch »

jeffreygoesto wrote: post #57
deng wrote: post #51

Earlier quoted context omitted.

German here. From my perspective it's hard to find - embedded systems programmers, meaning people who know real-time systems, have good C/C++ knowledge, know their way around the Linux kernel and are also able to do basic things with a scope. - good(!) C++ programmers in general - people who know devops and software development infrastructure C++ might not be sexy, but there's a vast amount of legacy software out the…

That is true. I found that for embedded C++ to be successful, you need to have some good (excellent sometimes was harmful, but that's a different topic) C++ _as well as_ good domain and optimization skills. It's a combination that is more and more scarce. C++ tends to be used in domains where size and speed matter. You need to know what the compiler and machine will do with your code to be fast. And what's more, only…

> I found that for embedded C++ to be successful, you need to have some good (excellent sometimes was harmful, but that's a different topic)

Why were excellent C++ skills sometimes harmful?

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