Metis and Me

For those of you interested in boot camps and switching fields, here’s a bit about where I’m coming from and how Metis has been so far.

Bio(graphy/logy)

I come from a biology/bioengineering background where most of my time in the lab had been spent moving liquids around via pipette or dealing with animals. In all honesty though, I find many aspects of biology to be beautiful and clever. Some of the coolest things biologists can do these days include turning neurons on and off with light (optogenetics), harnessing evolution to do our bidding (directed evolution), and easy gene editing (CRISPR).

The three big problems I had with wet lab biology were:

1. Doing biology meant focusing on a very small aspect of a very large system. Because biological systems could be so complex and messy, you had to take on a very small part of the system to be able to prove anything about it. And then, to prove you discovered something about this small part of the system, it seemed like you still had to do many many different experiments to draw the same overall conclusion.
   • In data science you take on a large system and try to figure out which small aspects affect it (e.g. feature engineering a model). Also instead of doing many experiments to draw one conclusion, in data science you can pull many observations from just one model.
2. A lot of the “debugging” had to be done after the experiment is completed, which leads to a lot of rinse and repeat. There are many experiments where you don’t know you messed up until you get to the results. And then there are usually no great checkpoints you can go back to, so you have to repeat the procedure again with minor tweaks. Additionally, just by the nature and speed of reactions, each experiment can take a long time to repeat.
   • In data science, you can set up as many checkpoints as you want! And running steps can be very fast (unless you’re training something with massive amounts of data).
3. Performing the experiments was a lot of menial labor. Planning experiments was interesting, analyzing results was interesting, but these two things constituted very little of the actual day.
   • Even the grungiest tasks in data science like scraping or cleaning data require a good amount of thought. There is also a lot of room for cleverness in terms of how you go about performing your task, which can be a fun challenge.

In addition to the improvement on these three issues, the universal applicability of data science is incredibly appealing. For biology (and many other fields), you are pretty much stuck in the same field because the techniques that you learn are not easily transferable to other disciplines. However, with data science, you can use the same techniques on all different kinds of data. Having the option to work in a biotech company or a gaming company or a finance firm is kind of amazing. Just a bit.

Metis

Even though I’ve been exposed to a lot of the curriculum taught at Metis before, I still think taking the boot camp holds tremendous value. The main benefits are:

• Practice, practice, practice. Coming from a field where I didn’t use a lot of programming experience outside of personal projects and my classes from college, getting forced to code every single day is a huge benefit to me and my skills. Even if I could program in the past, I can now do it faster with less mistakes.
• Learning what’s being used in the industry. Even if I knew the models and concepts of data science, it’s nice to know specifically what tools are trending in the industry. Being well versed in a particular library or flavor of SQL might just be the edge you need over another candidate with a similar skill-set.
• Learning to code with other people. We have an hour of pair programming every morning where we work on a coding problem with another person in our cohort. By doing this, it helps us explore other approaches to problems that we may have not considered. It also gives us a lot of experience with coding with other people which I believe to be objectively more challenging than working together on a presentation or a report.
• Career support. Knowing that they’ve helped a bunch of other people just like you with little or no relevant previous backgrounds land jobs, is comforting. They teach you how to network, how to linkedin, how to resume. They also encourage you to go out to events and give you the information about them, which is a great resource.
• Providing a support network. Your peers are all people coming from different backgrounds, aiming for the same thing. Having a network of people who are going through the same struggles as you is extremely valuable. We’re looking out for each other and we share resources (e.g. connections, information). Super. Awesome.

If you’re interested in learning more about what goes on at Metis, feel free to reach out! I’m at the SF campus and would love to chat over coffee or grab lunch with those who want more information.

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