A Former Data Scientist’s Approach to AI

Well, I want to hear that story, but I first want to start with data science because both cybersecurity and data scientists are things I feel like.

So I've been a programmer for a while and we didn't have a lot of roles other than programmer and IT sysadmin, you know, and there's so many more roles.

And sometimes I find myself just making assumptions about what it means without fully knowing.

So I think I fully understand what a data scientist is, but because I'm not 100% sure, I'm going to ask for the sake of the people, what does a data scientist do day to day?

Okay, I'm glad you asked that.

And I really like your pragmatic thinking on that front as

well.

But what I've learned, I learned when I was a data scientist in the companies I was at, is that data science also looks different in different companies.

It looks different depending on the domain.

Like I was in cybersecurity.

If I was in healthcare or a different domain, that could look different.

Depends on the scale of the company.

So, okay.

I was a data scientist in cybersecurity companies.

These are mostly... medium-sized companies, not super big, like about 5,000-ish employees.

But the data science teams that I was on were pretty small teams.

So what data science looked like on my team was I was...

So typically, a data scientist is building machine learning models of some kind.

With generative AI, I think that is a whole separate discussion as to what a data scientist means.

But back then, we weren't training foundational models.

We were training... like either deep learning neural network, deep neural networks or tree based models, simpler machine learning models, if you will.

And then your job was basically, yeah, like to train those models and maybe evaluate them.

But because I was on a smaller team, I think I got exposed to a little more of the end to end.

So we didn't have a data engineer on the team.

So I was also doing like the data gathering, cleaning, sanitizing, then actually training the model.

Well, I want to hear that story, but I first want to start with data science because both cybersecurity and data scientists are things I feel like.

So I've been a programmer for a while and we didn't have a lot of roles other than programmer and IT sysadmin, you know, and there's so many more roles.

And sometimes I find myself just making assumptions about what it means without fully knowing.

So I think I fully understand what a data scientist is, but because I'm not 100% sure, I'm going to ask for the sake of the people, what does a data scientist do day to day?

Okay, I'm glad you asked that.

And I really like your pragmatic thinking on that front as

well.

But what I've learned, I learned when I was a data scientist in the companies I was at, is that data science also looks different in different companies.

It looks different depending on the domain.

Like I was in cybersecurity.

If I was in healthcare or a different domain, that could look different.

Depends on the scale of the company.

So, okay.

I was a data scientist in cybersecurity companies.

These are mostly... medium-sized companies, not super big, like about 5,000-ish employees.

But the data science teams that I was on were pretty small teams.

So what data science looked like on my team was I was...

So typically, a data scientist is building machine learning models of some kind.

With generative AI, I think that is a whole separate discussion as to what a data scientist means.

But back then, we weren't training foundational models.

We were training... like either deep learning neural network, deep neural networks or tree based models, simpler machine learning models, if you will.

And then your job was basically, yeah, like to train those models and maybe evaluate them.

But because I was on a smaller team, I think I got exposed to a little more of the end to end.

So we didn't have a data engineer on the team.

So I was also doing like the data gathering, cleaning, sanitizing, then actually training the model.