How I Quit My Career and Decided on Data Science (Part 2 of 2)

This post was originally published 22-April 2020.

This is the second of two blog posts: “How I Quit My Career and Decided on Data Science”. In the first post, I gave a brief overview of my career and described the key events that led me to decide to quit my job. In this post, I fill in the gaps between quitting my job with only a vague idea of what I wanted to do next and how I decided to enroll in a data science bootcamp.

If you’re interested in Part 1, you can check it out here. If not, here are the bullet points:

• After 7 years and a variety of professional roles, it became abundantly clear that I didn’t like the career path I was on.
• Upon reflection, deliberation, and support from loved ones, I decided to quit my job and take some time to sort out what I wanted to do next.
• This wasn’t a shotgun decision. I saved enough to myself a 6 month financial runway.

Looking back, my funemployment, which started late-November 2019, had 4 general phases:

• Reflect and recharge, which was characterized by getting back to the basics — healthy diet, exercise, doing things I love like snowboarding and reading
• Explore my options, which was mainly a process of looking back on where I’ve been and narrowing the target for where I want to go
• Vet my options, which was testing out ideas for where I wanted to go next via online courses, informational interviews, etc
• Make moves, which was pretty much bootcamp recruiters and applying

These phases will serve as the outline for this post.

Reflect and Recharge

As I mentioned, my official funemployement started late-November 2019, just before the holidays. When I went home it was lots of catching up with friends and family. One of the common questions I got was: how’s work going? I’d say I recently quit my job. Naturally, the follow up question was: what are you going to do next? The truth was, I didn’t know.

The degree to which I expounded upon this truth was very much dependent upon who I was talking to. To some, I’d say I’m exploring starting my own business in operations consulting (which, admittedly, was a bit of a cop out). With others, I’d level — honestly, I don’t know. What I do know, though, is that I wasn’t happy in my old job and knew that I needed to take some time off to figure things out.

With the latter group, I was surprised with how many people responded by saying something to the effect of: Wow, that’s awesome. I wish I had the courage to do that. This struck me because I never viewed the decision to quit my job as courageous. To me, it was necessary for sustained mental wellbeing. It also illuminated to me how many people aren’t fulfilled in their work. I digress though.

These conversations prompted some deeper, more philosophically informed questions for me — What do I want out of a career? What do I value in a job? How can I use my work to make a positive impact on the world around me?

Obviously the answers to these questions aren’t straightforward. I ruminated on them both passively (e.g., while riding the chairlift at my favorite ski resorts) and actively. One of the most fruitful exercises I did was a day-long whiteboard session. I asked myself two questions: What gives me energy? What do I want?

Forcing myself to actually put these thoughts into words created a lot of clarity. Here were my key takeaways:

• I am energized by creative work (both professionally and personally)
• I am energized by problem solving in a systematic way
• I want a career in which I can continue developing and refining my skills
• I want a job that is founded on a set of objective, technical skills
• I want a job with autonomy and flexibility

With that, I had my guidepost and was ready to explore.

Explore my options

The aforementioned guidepost pointed me toward two alternative paths to explore. Path #1: Entrepreneurship. Path #2: Programming.

Entrepreneurship has always excited me. As I mentioned in Part 1, I’d had some entrepreneurial experience working as a freelancer and even co-founding a company. All of that experience, though, was cursory and always a side hustle.

The notion of starting my own business excited me. I had some expertise in business operations and consulting experience so the idea of starting an operations consultancy for small businesses was a viable option.

By the same token, I was drawn to programming. The coding skills, logical approach to problem solving, and market-demand appealed to me. I’d dabbled in some coding in the past and enjoyed it, but never really took it too seriously because it didn’t relate to my day-to-day at work.

In the beginning, I pursued both paths with the same vigor. I spoke to entrepreneurs and coders alike about their jobs. I did my online research. I took online programming courses. I considered the pragmatics — opportunity costs, startup costs / initial investment, time to profitability, etc.

It was a long and thorough process but suffice it to say I chose path 2 — programming. At this point, I didn’t know specifically what aspect of programming but I had my north star, albeit a bit blurred.

Vet my options

By now it was February. My reflection and exploration in the previous months had me energized. I knew it was time for me to get serious about vetting my options for my next move.

I can sometimes have a tendency to dive into new things with an enthusiasm and vigor that quickly wanes once the “shiny factor” wears off. In order to safeguard against this trait, I committed to taking a methodical approach to vetting my options on my path to making a decision.

The decision funnel looked something like this. Spoiler alert — I chose General Assembly’s Data Science Immersive. Here’s a high-level breakdown of each point along the decision funnel.

Entrepreneurship or programming? Covered that one above.

Software engineering or data science? I’d been exposed to data science in some of my past roles and was fascinated by it. It was more of a black box to me that software engineering so I dug into it. I loved how it combined programming, math, analysis, business acumen. When I asked myself what kinds of problems do I want to solve? The answer was data science problems over software engineering problems.

Self-taught or provider? One of the common threads in my research on getting into data science was that you can learn the material on your own — there are plenty of quality resources on the internet. This was an appealing option, mainly because I wouldn’t be spending thousands of dollars. Alternatively, I knew I wouldn’t be able to get the depth of knowledge I desired. So I chose going through a provider.

Part-time or full-time? For a fleeting moment, I considered what doing something part-time would look like. It would mean I could get back into the workforce more quickly and reskill outside of work hours. Then that moment passed. I’m the type of person that does best when I’m totally immersed in something.

In-person or online? There are tons of great data science bootcamp providers out there, both online and in-person. The online aspect was appealing because I could learn from the comfort of my own home. I ultimately decided in-person, though, because I wanted that stronger sense of community and relationship building that happens with in person interaction. (This was before the COVID-19 pandemic was talked about in mainstream media…)

Which in-person provider? I had 3 options: General Assembly, Flatiron School, Galvanized. Based on online reviews, they all seemed to be a great option for me. I ultimately chose General Assembly because it was the best fit for my situation.

Make moves

When I decided I wanted to enroll in General Assembly’s Data Science Immersive it was early March. The application deadline was three days away and I was leaving for a family vacation in four days. It was time for me to make moves.

Thanks to great guidance and responsiveness from my awesome admissions producer, I was able to turn an application around and interview within a matter of days. Then, the day before I left for vacation I got the positive news that I was admitted!