Started as a Bartender, Now I'm Here
Tags: career, beginners, datascience
Published: 2022-11-07 02:55:28

## So how does someone who used to be a bartender end up here at [Flatiron School](https://flatironschool.com/)?

Before we get into that, I’m **Jon**. I like spending time with my family, being outside, and coffee. I recently decided that I was ready for a career change and I was hoping to make it happen soon (I’m not getting any younger)! Coming from a career in bartending, then retail with crazy hours, long commutes and very little work/life balance, I found myself contemplating which direction I should go. After weighing the potential options of trades, bootcamps, formal schools, or just trying to break into another industry, I decided I wanted to commit to a tech bootcamp to accelerate this process. I’m basically brand new to coding so I think the bootcamp route will be the quickest and most effective way to learn these new skills.

## But which bootcamp?

I ended up deciding to look into data science bootcamps after my partner suggested it to me. The main reasons she gave for pointing me in that direction were my logical thought process (a good match for data science) and that data science jobs are high-paying and often go unfilled at her company. In addition, after digging into the field of data science, I found out that it was an incredibly interesting field and can be applied in almost any industry. At a high level, data science leverages technology to collect, understand, process, and communicate findings from data. One of the most eye-opening use cases I found about the true power behind data science is  combining the knowledge of top cancer researchers with machine learning tools to help identify and classify early stage tumors in patients. Talk about making a difference!

## Data science is in demand:
According to the U.S. Bureau of Labor Statistics-Occupational Outlook Handbook, data science employment is projected to grow by 36% (40,500 positions) from 2021-2031 which is much higher than average. The pay is also good - the median pay for data scientists was $100,910 per year in May of 2021.


[![BLS Preferred Citation](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/96v7gucm7ejcfge75fc2.png)](https://www.bls.gov/ooh/math/data-scientists.htm)

## Why Flatiron School?
Flatiron School was recommended to me by a friend and after exploring a few other options, it seemed to fit me the best. Through Flatiron School, I can complete an entire data science bootcamp in just 15 weeks and they offer a career prep and coaching service that will help to land my first job in the field after successful completion of the program. Throughout the program I’ll be building a portfolio so I can easily share polished examples of my work. I’ll get to participate in mock interviews to make sure I’m ready to communicate my skills and technical knowledge in future interviews. The fact that this career prep process is a major part of the curriculum and spans from the very beginning to after the program makes me feel at ease about starting a career in a new field. 

## Why data science plays to my strengths:

Working with technology - Technology is the future. In this field you’re required to stay current with and implement new technologies. I’ve always loved keeping up with and integrating new technologies into my daily routines so this falls into one of my strengths. After just the first week of class, I’ve already worked with a few new-to-me technologies which include: Python, Terminal, git, GitHub, and Structured Query Language (SQL). 

### Team Player - 
It’s all about the collaboration, man! I’m an effective communicator and I am flexible in group-work environments. If you can see the big picture, an individual contributor working as part of a bigger team is very rewarding and the collaborative effort of the group tends to be much bigger than the sum of its parts.

### Curious Mindset / Analytical Thinker - 
In my free time, you’ll typically find me with my nose in a book or a podcast in my ears trying to learn about my next interest. Before I dive in to tackle a problem, I like to have gathered information and asked my own questions about it. In data science, the typical workflow works similarly. There is always something to learn and better techniques or technologies to choose from.

### Math / Science - 
I’ve always enjoyed math and science and I’ll be able to put these skills to use in data science which relies heavily on statistics, probability, linear algebra and calculus. 

## My time so far:
Before the course starts, admissions sets you up with 60+ hours of coursework to work through. This allows you to gain some important knowledge and dip your toes into the subjects that will be covered during the first week or so of class. This pre-work went pretty smoothly for me and left me feeling excited for the course to come. After finishing the required pre-work a packet of additional resources becomes available and I reviewed many modules of that to make sure I was ready for day one. 

### The pace is fast.
I can’t say it enough, the learning pace is so incredibly fast. I was told this in advance, but this is a new level of fast. It’s fun and exciting to come in and learn so many brand new concepts so quickly and to be able to start implementing them right away. 

### Unexpected
The thing I didn’t expect from the Flatiron School is the level of community involvement that happens in Slack and other virtual environments. I guess because all of my previous education and work has been in person, I wasn’t sure of the culture I’d find in an online setting. It doesn’t disappoint. 
I also wasn’t ready to be in front of a camera all day. I’ve had adverse feelings toward meetings on camera and wasn’t sure if I’d ever get used to it, but by the end of the first day I was fine. I’m now super comfortable with having my camera on and it’s nice getting to see everyone learning with you.

### What I’m looking forward to:
I’m already making connections with with the students in my cohort and I’m looking forward to making those stronger. I’m also looking forward to diving deeper into the material and using the knowledge I’ve gained to create a data science workflow from start to finish. 

## Cheers!
### (and no, I won't make you an old-fashioned...)

![Old Fashioned](https://media.giphy.com/media/T7a5mknrNZG4Oaz3zo/giphy.gif)