Why Data Science?

$ whoami_

In 2015 I started my professional career with a mostly-undefined IT position.

The department I was working for knew they wanted an intern but really couldn’t figure out what exactly for.

After weeks of “Look busy™” and “Put this into a spreadsheet,” they ran out of busywork. As my internship came to an end, I had managed to impress a couple of other departments heads by coding some extremely basic HTML. HR decided that, no matter how little the IT department had for me to do, they wanted me to stay SOMEWHERE.

At first, I was offered a shot in the robotics department - I’d always been a fan of robots and any kind of automation so I was extremely hyped on the opportunity.

The day came for me to start my robotics internship, 8AM sharp!

9Am

10AM

11AM

At 11:30, HR informed me that someone was FINALLY coming to get me!

A little late, but I could deal with it.

At last! In walked …

An engineering manager?

As it turned out, the robotics department had decided against allocating resources for any interns that morning.

I was disappointed that I wouldn’t be getting my hands dirty in any PLCs or risking my hand around any pneumatics, but it all turned out to be a blessing in disguise.

As it turns out, I had some, albeit minor, engineering experience. I was able to help out some of the other starting interns in brainstorming and the tales of my extremely basic knowledge of vaguely how computers worked sometimes had made their way throughout the engineering department.

A few of the people were doing some data entry tasks and there was an entire department for data processing and workshops.

I spent the next several months bouncing between engineering tasks, data collection, and data processing before I decided that it was unbearable to read some of the production operators handwriting (mine isn’t much better and I can’t really blame them, their hands have enough to do).

I decided it was time to make an entire system from scratch.

Well, mostly scratch.

my_first_data_project.ipynb

Our data department had a horrifically optimized Google Sheets page for every production area. This data was all input manually from one of the supervisors and then verified by one of the data analysts.

Man this isn’t very efficient, is it

- me, while holding 5 sheets of paper that are for one week

Enough was enough. I was going to learn JavaScript. And I was going to use a poorly optimized Google Sheet as a database.

This side project became my magnum opus. I took on responsibility after responsibility as I added to the functionalities of a site that should have never existed. For anyone reading that isn’t already aware, if you are ever asked to use Google Sheets as a database - run.

The further, the faster, the better.

I went into that project knowing absolutely 0 JavaScript. Afterwards, I feel like I somehow knew less.

There was something I learned a lot about over that process though -

Data

Since that catastrophe of conflicts and an ungodly number of requests that, at best, didn’t make any sense, I’ve been putting my brain to a litany of data projects. All to scratch that itch of the “What’s the best way to do this” question.

“What’s the best time to fish during the winter in Project: Zomboid and what are my exact odds of catching something? Is it actually worth it to even try during the day?”

“How many Pokemon did I catch during my last play session? What’s my remaining percentage and what are each of their odds betwene catch rates and encounter rates?”

Or even “Is there a good way for me to catalog the available XML data of customers in our contact-base and how can I best search all of the client comments for the customer type I’m interested in?”

Every time I approach any kind of issue, I ask myself two questions.

Can this be easier?
What’s the best way for this to be done?

next_steps.edu

Since 100% of my background has either been personal or not fully formalized, it was hard to find next steps forward. As I found myself out of a job at the end of 2022, I decided it was time to put some stake in my passion for Data Science, and get some career direction along the way.

Starting Feb 20, 2023, I began a 15-week intensive Data Science bootcamp to completely dedicate my Data Science interest into something that’s marketable.

At last, it was time for me to go from Data Science Geek to Data Scientist