Data Science Has Changed - Here's What to Do

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[SeanWalberg]

The key is to be a "T shaped" person. Deep knowledge in a particular area, but a broad knowledge in the adjacent areas. Goes for almost any job in technology; we're seeing the same changes over on the infrastructure side of the market!

[Zale]

00:00 Data science job outlook is changing rapidly and it's important to know what to do.
00:14 Data science jobs are not getting automated, but the job outlook is changing.
00:29 More data and insights are available, but humans are still needed to interpret and utilize them.
00:57 Exploratory data analysis is not as important as before, but understanding Python code and libraries is crucial.
01:27 Building projects and having skills are more important than just having credentials and spamming projects.
02:21 Data scientists need to have software architecture skills and be able to build full applications.
03:04 Coding is getting faster, so companies will need fewer people to write code.
03:44 Knowing how to put together different components and building actual applications is crucial.
04:12 Traditional analytics is getting easier, but it's merging into building full applications.
05:04 Learning data science and building applications simultaneously is important.
05:32 Being really good at your job and building full applications is essential in the changing data science landscape.

[codelucky]

Here are the six most important points from the video:

• Data science jobs are not dying, but the job outlook is changing rapidly.

• Exploratory data analysis is becoming easier and faster with the help of machine learning models.

• Companies will still need human data scientists to build and put together Lego blocks of data, as chatbots cannot do this yet.

• Data scientists will need to know software architecture skills, libraries, frameworks, and languages to build full applications.

• Traditional analytics is merging with building full applications, and data scientists will need to learn how to do both.

• To stand out in the job market, data scientists should learn advanced machine learning architectures and build their own technologies.

[jja]

The problem lays in that building simple analytics and simple models are the not the tasks of a "Data Scientist" these are a the tasks of a Data Analyst. So yes, Chatgpt can obviously replace a Data Analyst. In fact there are thousands of jupyter notebook templates that can be used to do this without the need of ChatGpt.

[Butimnotatrader]

I have to disagree, my recruiter told me there are A LOT of people getting fired because they are using ChatGPT to get jobs but can’t keep them because lack of skill

[elizabethmorales]

Thank you for the video! Everyone keeps talking about how AI is changing jobs, especially in technology, but you are showing us what to do. It would be great if you could make a video about pipelines, etc. Thank you!

[rossgo]

Absolutely agree!

I think abundance of online training sites (DataCamp / Coursera / Udemy) has made good fundamentals of data science fairly easy to find now from a recruiters perspective. I'm doing my AWS Machine Learning Certifcation at the moment and the cognitive leap from visualisations and hyper parameter tweaking to understanding full-on data application architectures and deployments is sort of staggering. The basics is stuff I sort of hope they might need, the big applications is what I know they will need.

[chloewei]

This is super helpful and thanks so so much! Would really love to see a part 2 deep dive into this topic if possible <3 Thank you!!

[Mrnafuturo]

I'm sure how good Python is, but few people talk about R as the default option when it comes to performing real data analysis using out-of-box packages.

[ThinkingFella]

My personal plan is to combine my currently ongoing programming education with my art-school education because I believe there is still a lot of untapped potential there. And I honestly don't even expect to find a decent job with those credentials in this economy, even though I believe combing X with programming e.t.c will be the future for X. I dunno i still suck at programming anyway lol

[raser]

Hey Greg, thanks for this video. It gives me a little bit of direction in these trying times. I am a industrial engineer graduate who became a software engineer and am now pursuing MS in computer science - but I am struggling to decide if I should take more software engineering type stuff or more analytics. Due to how rapidly the analytics space is changing, I think my best move would be to just focus on becoming a full stack engineer

[senna_william]

Good stuff as always! Can you give us a spoiler about what problem the startup you are working on solves?

[Werepizzaa]

Hey thanks for this video. This whole space is really muddy and hard to get a clear idea from someone who actually knows what theyre doing. Thank you for sharing and I really hope to apply this

[mikekertser]

The main question is - how to get a first job in DS without much experience, even as unpaid intern?
It turns out, that nobody actually wants inexperienced workers. Most of the companies, especially startups, want the job to be done.

[ReeSean]

Hello,
I come from a different background in Mechanical Engineering and am pursing a MS in Data Science. It feels like we are learning very superficial Data Science of knowing stats, ML algorithms, and how to apply the ML algorithms. I worry that I am going to graduate with just knowing baseline models, without making a project of my own.

You had mentioned, instead of this superficial knowledge, to build full applications. But can someone explain what a full application entails and a typical structure/plan for how to build such application?

Much appreciated

[Tamicheal]

Great stuff, I have been serving two roles for my company for a while, one is business analytics ChatGPT made that so much easier for and now I have time to do my real job.

[datapro]

Greg is right. I don't see that a lot has changed however. A full stack developer has a lot more opportunities than other folks.

[sheikkhader]

that's true! aligning the people in the right direction!

[MichealAngeloArts]

The "hire a data scientist to build a full data product" thing only exists when we talk about start-ups, where this is only done to save heaps of money that would have otherwise been sucked up by highly skilled and highly earned developers, architects, and data engineers. It will never exist when we talk about medium-to-large enterprises, where no stakeholder on planet earth will ever trust a customer-facing application built solely by data scientists.

[Dreadheadezz]

I’m about to graduate with my bachelors in data science. Definitely needed this