Learning is Intangible

For this post, I’m refocusing for a moment on my full-time job. I know that this blog is mostly filled with my hobbies and personal projects, so it might seem like those are the only things I do. However, most of my life actually revolves around my career in tech.

I started my internship as a data scientist at the beginning of the month. It’s my 2nd full-time job as a computer scientist, and in some ways, I cannot help but compare it to my 1st full-time job. I worked as a front-end software engineer for over two years in a smaller company. Both companies are great, filled with talented people I get along with. More importantly, in both companies I am doing work that I am passionate about even though they are different.

And that’s what I want to focus on in this post: the difference between my experience as a front-end software engineer from a small start-up(-ish) company, and my impression so far as a data science in a much, much larger company.

I knew that the work would be different. And yet, I think I naively assumed that the job would be similar enough that I could measure my productivity in the same way. In my old job, I knew I was being productive when I managed to finish my assigned tickets. Depending on the tasks, I could finish about five moderate bugs in a day; for new features, I could at least get some new code out to code-review within a day or two at most.

In my new job, the process is entirely different. We’re working in Kanban style, rather than sprints. My tasks are a little more vague. Instead of having a specific goal I could measure, like changing the header background from white to grey, or adding a pop-out to a link, I’m assigned tasks like visualizing the clusters of similar items. As you can see, this task is less measurable. For one thing, the end goal isn’t to just have a nice visualization, right? Underneath that statement, I know that my goal is also to analyze the visualization, to obtain insights from the clustering. And this means that I have to find out a clustering algorithm that can actually give me a good visualization; it means that I have to find the data that can work with such an algorithm; it means that I have to find a visualization that can actually give me insights. And in the end, how do I know if the insights are meaningful or not?

For the past four weeks, I have struggled a little with this vagueness. Yes, I know I could ask, but I get the impression that it’s also part of the job of a data scientist to figure out these things. Whenever I’m assigned a task, it’s no longer up to a product manager to break down that task for me. It’s up to me to figure out what’s involved in that process.

I think this is the biggest difference between my previous job and the current one. As a junior software developer, my job was to implement whatever the product managers told me to. This is in contrast with a research position, where my job is to discover what must be implemented.

I worry that I’m not being as productive as I can be, and my worries are compounded with the fact that I don’t actually know how to measure my productivity as a data scientist. Which leads me to this passage from The Lean Startup by Eric Ries.

When I worked as a programmer, that meant eight straight hours of programming without interruption. That was a good day. In contrast, if I was interrupted with questions, process, or — heaven forbid — meetings, I felt bad. What did I really accomplish that day? Code and product features were tangible to me; I could see them, understand them, and show them off. Learning, by contrast, is frustratingly intangible.

Wow. This book is required reading for my Technical Entrepreneurship course that runs alongside the internship. I don’t have much of an entrepreneurial spirit in me, but when I read this, I thought, “Aha! This is why this book is required reading!” I never realized what it was that bothered me as I started my career in data science, until I found this passage in the book. I could have never put it in a better way.

Learning, by contrast, is frustratingly intangible.

I realized much of what I do in my new job as a research intern is learning.  When you’re researching, what you’re doing is learning. You’re learning what works and what doesn’t. I was so used to measuring my productivity in terms of how much code I write or how many tasks I finished. Now I have to figure out a way to measure my productivity in terms of learning and the return value from what I learn.

2017 May Reads

Alright, in an effort to liven up this blog from my incessant writing woes posts, I’m going to take a moment to talk about some of the books I’ve read this month so far. I think if I read really quickly, I might be able to read one more book before the month is up.

27833542 Story Genius by Lisa Cron

I’ve been having a lot of difficulty writing the first draft of my story, mostly because I had a hard time really writing from any of my characters’ perspectives. This book was recommended to me in response to that.

I think the most valuable lesson I learned in this book is how every story that captivates readers sufficiently is ultimately a character-driven story. I’ve read many writing books before, and some of them distinguish between “plot-driven” and “character-driven” stories. In Story Genius, Lisa Cron explains why any kind of meaningful story is actually character-driven, no matter if the plot has tons of exciting things going on.

I know, it’s not a ground-breaking concept. Even in my own reading experience, I tend to gravitate towards books where I sympathized with characters the most. And I think her explanation brings home why this is so: an event in a story (in other words, the actual plot) has very little meaning unless the character gives us a context in which to make sense of that event. So really, even your most plot-driven story, if it’s good, is actually anchored by the protagonist.

Other than that, I feel like this book doesn’t offer anything else that is truly unique that sets it apart from other writing books. I think if you’ve read other writing books before, the bulk of the book after the first several chapters would feel achingly familiar. I’ve also seen other reviewers point out that they would have liked to see actual neuroscience explored in this book. I have to agree that the title and subtitle give off a more scientific vibe than what I got. Most of the time, the author would only say things like, “it’s brain science!” or “our brains are wired to look for this and that.” Now, while that was sufficient for me, because all I wanted was to learn writing techniques, I can understand why others might be frustrated about it.

The Queen’s Thief Books 4 & 5 by Megan Whalen Turner

It’s difficult for me to review these books, because there’s just so much to say. I feel like I’m not going to say anything that haven’t been said before, which is unfortunate, because this series is my absolute favourite, and I feel as if I should be able to say something more personal about it. But I can’t, not succinctly anyway.

In A Conspiracy of Kings, we follow Sophos, the heir to the throne of Sounis, as he is sold into slavery by rebels. This book is my 2nd most frequently reread book in the entire series (yes, even more so than The Queen of Attolia, which I know is the favourite of many many fans of the series). But there’s something about Sophos’s character that just calls to me. I mean, Eugenides is impressive and amazing and I love reading about his tricks and cleverness. But Sophos feels so much more human in comparison, and more relatable in that aspect. His earnestness and even his naivety made me root for him throughout his entire journey. And I feel that because he doesn’t begin as this awe-inspiring figure in the same way Eugenides had always been, Sophos’s character arc then becomes more pronounced. The climax of this book is one of the best things I’ve ever seen, and I almost keeled over seeing how Sophos manoeuvred the difficulties of his situation.

Thick As Thieves is the much awaited (and I mean 7-year-wait) fifth book of the Queen’s Thief series. Similar to the two previous books, we have a brand new protagonist in this book: Kamet. Many people would remember Kamet from his little stint in The Queen of Attolia as the slave and secretary of the antagonist, Nahuseresh. Thick as Thieves follow Kamet’s adventure as his life as a slave is turned upside-down when he finds himself fleeing for his life from the Mede Empire. This book echoes The Thief moreso than the other three books in narration style and the types of twists that had been pulled. Much of the book is about the adventure, and very little political intrigue, unlike QoA, KoA and ACoK. Since this is just my first time reading this book (and I’m sure that like the other books in the series, this one can only get better in rereads), I have to say I’m a little underwhelmed by Kamet as a protagonist. I think I say this, because I read TaT almost as soon as I finished ACoK. And like I said above, Sophos is so, so dear to my heart, and Kamet just had very big shoes to fill. I found myself reading more for the sake of Kamet’s companion (I believe it’s a spoiler if I reveal who it is), than I did for Kamet’s sake. That said, I believe that eventually I’d warm up to Kamet like I did to Costis in KoA.

Writing Woes: Somebody’s Getting Axed


Well, I think I’m realizing more and more how isolating an endeavour writing can be. Considering how many times I’ve fallen into writing angst in the past several months, I think it’s safe to say that I’m far from the image of the highly energetic, happy-go-lucky writer that I imagined myself to be while working on a fun, light-hearted adventure story. Clearly, I’m not have as much fun as my characters, that’s for sure.

And it seems as if several of them won’t be having fun any longer either.

Continue reading “Writing Woes: Somebody’s Getting Axed”