Long term career investment through curiosity
Looking back at some of my proudest moments in my professional life, it’s hard to explain exactly how they came to be. There’s always non-linearity, lots of uncertainty, and chaos. In an attempt to find a common thread and what could be repeatable, it could be that I followed my curiosity and made my own path.
Writing a book
I’m very grateful that I got the opportunity to write a technical book about machine learning interviews, published by one of the most well known tech publishers, O’Reilly.
What led up to the process though, was many years of writing related hobbies.
- I started this blog in 2017. One of my earliest posts: Passing the CFA level 1 exam with 6 weeks of study.
- For my video game studio, I’ve written multiple story scripts, each of 70k+ words.
- Since high school in Taiwan, I’ve been writing long form posts and stories on the internet. Here’s a little piece of internet history for you: Wretch blogging platform (RIP)
I think that without my long history of consistent writing on this blog and on LinkedIn, I wouldn’t have been selected to be an author, especially in a topic as hot as machine learning interviews.
What informs the content in my book also comes from my free time: I’ve had 80+ coffee chats with folks seeking advice to enter machine learning, or to grow in their careers. I’ve had to wind down this commitment since writing my blog, newsletter, and books can reach more people, but teaching online courses on O’Reilly and Maven where learners can interact directly with me achieves similar goals.
Of course, there’s also the broad range of experience I gained professionally, being principal data scientist in 2 companies, and interviewing 70+ candidates on the other side of the table. Having worked full time in 3 companies, I’ve also interviewed a lot in order to get those 3 job offers (and more), experiencing a wide range of interviews that I’m putting into my book as well.
All of this isn’t easy for others to replicate. To put it bluntly, there’s a lot of career advice being offered by people that haven’t walked the walk.
The summary? It seems like it started with following my interests in writing, without knowing what the payouts would be; and not even expecting a payout… It doesn’t matter whether it’s fiction or non-fiction; there are highly transferable skills with either type of writing.
Recently, I posted a blog post I wrote in 2020, Practical thoughts on career door-opening - even without knowing one’s ‘passion in life’. I think it’s still relevant now. The gist is that it’s good to do some things that open doors later down the road, even if you’re not sure what to do with those opportunities just yet. Optionality and freedom to choose is the key.
After posting this, a few readers reached out to me with their thoughts. One of them asked me what are good doors to open in the professional world (since the blog post mainly used the analogy of education).
I’d say that the doors I opened that helped me gain more responsibility in my professional life were:
New grad: Differentiating myself and gaining trust in technical skills
I started technical speaking internally at company journal clubs, and at Aggregate Intellect’s meetups. The quality and detail of those presentations helped build trust that I could take on more responsibility. That trust in my technical skills helped me land and deliver on large projects that I think aren’t often available to new grads, thus fast-tracking my career many years ahead.
Senior DS: Differentiating myself with more software development depth
The terms “career track”, “career path”, “career ladder” implies one’s career is very linear, but I find it better to conceptualize my career as a boat I’m steering in unknown waters. You could make a stop at an island and look around just out of curiosity, if you’re not afraid of the hassle. You might find bounties on that island that helps you later in the journey.
After my first full time job, I worked on a full-stack developer contract. Due to that experience, I was able to increase my end-to-end ML skills, which was highly valued in a startup environment. I gained responsibility quickly and was trusted with shipping updates to our production ML apps that was serving customers live and adjudicating millions of dollars.
In addition, I continued to gain experience with shipping ML and projects. One surprising thing that helped was game dev (once again, paying dividends). As part of my game studio, I’ve faced tons of common problems and solved them, such as releasing a bugfix on the day of the big launch! A player DMed me on Steam saying my Steam achievements weren’t working. Lo and behold, I had forgotten to include the libraries when building the final distributable files. I sweated, and quickly fixed it. This makes this kind of scenario at my full time job less stressful, since I’ve been there before.
What a sweaty palms day, fixing a bug on launch as the solo developer.
Principal DS: impact at scale
When I was interviewing for principal data scientist roles, a common thread of the job postings was that the candidate demonstrates technical leadership both within and outside their company (on top of required technical skills). I also saw this trend in senior manager roles and above, where “industry influence” was expected. Thanks to my previous experiences in speaking, this was easy for me to demonstrate. Another way I opened doors as a senior DS for this role, was reading how I could impact my team at a larger scale. Here are recommended sources:
- From entry level to senior+ developer - Multiply impact with developer leverage
- The Effective Engineer by Edmond Lau
- StaffEng website run by Will Larson
- The Staff Engineer’s Path by Tanya Reilly (This book was published after I had been promoted to a principal DS at a previous workplace, but I’ve read it in order to become better and I highly recommend it.)
So, I’d say that public speaking opens doors, on top of the required relevant work experience leading teams, mentoring team members, shipping projects to production, and more.
Stage fright? What do my hobbies have to do with it?
One random thing I hadn’t thought much about was stage fright; I have it, but I know how to deal with it. People will likely deal with stage fright initially once they get started with public speaking; it’s through facing uncomfortable situations that we can gain the skills that aren’t so easily available. Funnily enough, I also had some experience with this through hobbies…
I played electric guitar in high school, and went from not knowing anything to performing in front of 700+ people in a year. There were free lessons provided by my high school club (taught by seniors/senpais), so I learned there. I had a $40 (CAD) cheap guitar and amp, and later borrowed a friend’s uncle’s Ibanez guitar (made in Japan).
In university, I performed a couple of times at the Bombshelter pub, which I recently learned has closed down… RIP
At the Bombshelter Pub. I played guitar and sang backing vocals for a friend.
In summary, following my curiosity and interests, help me become a better, well rounded human. This just so happened to help me in my career, which is a thinner slice of me as compared to my whole self as a human. Who’d have thought?
Starting my ML career
I studied economics, and didn’t really know what I liked. That changed in my 3rd year where I finally shaped up and stopped failing courses. (I’m not kidding, I’ve failed 2-3 courses, which I retook and passed.) I also got interested in econometrics, which I didn’t know at the time was closely related to machine learning, because it’s pretty much applied statistics for economics.
I also followed my interest in programming to make video games, even if it wasn’t my major. I think university is a great time to start learning things you wouldn’t otherwise have exposure to: many of my friends and professional network have mentioned regretting not taking more electives in university. If that wasn’t possible (looking at you, Waterloo engineering), there’s still a lot of chances to do so while working! Who knows what you could find within yourself.
I’ve written more here on how I entered the ML field:
The summary: Following my interests in gaming, which led to programming, despite not majoring in it. Also, shaping my major to focus on what I was interested in, econometrics. Working hard to do well at both the courses that I was interested in, and not interested in but required.
This ended up being a long post. Thank you for reading! If I had to sum up this summary, it’s that taking the road less travelled and gaining broader experiences early on, could unexpected help in leaps and bounds further down the road.
This showed in public speaking helping me gain the same skills to influence product leaders within the company, communicating clearly to my team and cross-functional teams, and more that helped me with delivering big projects and gaining more responsibility. I built solid developer skills through hobby game dev and full-stack dev, which helped me in my career.
I enjoy my hobbies regardless of if they have payout, like video games that cause me to spend money. Just bought an RTX 3080 Ti. Though I think that online multiplayer games are great for working cross-timezone, cross cultures, and wrangling schedules – useful skills! As mentioned in the examples in the articles, it’s not about if you think there will be payoffs, it’s following genuine curiosity regardless.
Overall, I think following your curiosity, and setting aside some time to grow outside of the beaten path, is the common thread. What that means for you, is up to you!
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