Starting things off
Well this is going to be my first post. As I’m sure lots of first time bloggers have run into, you feel a lot of pressure to make the first post amazing. You feel the need to start with a great first post, because you’ve told all your friends you’re going to make a blog, and some of them are eagerly awaiting that first post. And then pressure builds…
Let me give a brief introduction of who I am. My name is Dorian Brown, and for about a year now I get to officially call myself a data scientist (atleast that’s the title at my company). I’ve been living in the Netherlands for about 10 years in a small student town called Leiden near Amsterdam. It’s worth a visit for a day if you’re ever in the area. I studied theoretical mathematics here which I enjoyed a lot, and focused mostly on probablilty, statistics, optimization and algorithms.
After finishing my master’s degree, I ran into the problem I’m sure many of the people reading this will have also run into: what do I want to do with my life? Unsurprisingly, I’m still trying to figure that out, but luckily I’ve made a little progress in the last few years. My first job was with an engineering firm which is contracted by companies which want a pipeline laid from A to B, usually over a sea floor. The “get down to business” mentality was great, and I really enjoyed the engineering culture there, but I quickly realised that I was missing a lot of experience in data-fu, and if I wanted to get better at that this wasn’t the best place to learn.
After a year I got a job at a dutch bank as a data scientist, and so far I’ve been able to learn a lot. Traditionally banks have been relatively old-fashioned, but in recent years they’ve been feeling the pressure of so-called fintech start-ups. This competition has caused them to try and modernize, which is very encouraging to see.
What this blog is about
So enough about me, you’re probably more interested in what kind of content you can expect to find here. Although the overarching theme is going to be data-science and all the stuff related to it, I’ll try and organize content in the following categories.
I’ll start these posts out with a question and a dataset, and at the end of the post I’ll post a conclusion (with an answer to the original question if we’re lucky). For all of these the code will be available on my github account, and in the post I’ll try and show the more interesting bits of analysis/code, and keep the uninteresting stuff hidden.
I’ve realised that I love the technical stuff about the data science profession. I realise it’s a pitfall to concentrate to much on the tools we use, and not enough on the actual question and the “real world” stuff, but I guess I’m a bit of an engineer myself. I often have discussion with colleagues on stuff like code formatting, R vs Python, new developments in software tooling, etc. I’ll try and share some of that stuff here too!
Although lots of the really theoretical stuff I learned during my studies has eroded from my brain, it still does help a lot with the work we do. I’m not going to be publishing my own papers any time soon, but I like to read about new developments and things relevant to the data science community.
I’ve noticed that since the data science profession is new and somewhat undefined, lots of people in this field run into problems within their organizations. This can range from things like unrealistic expectation (data scientists are the magic bullets that can solve all our problems!), what work falls within a data scientists job description, how to manage a team of data scientists, etc. I think if we all try and share the kind of things we run into, and what some good approaches to solving these problems are, it will help us all be better at our work.
Rounding things off
I hope you guys managed to keep reading this far in. This was my way to conquer the whole writers block, and to give my a blog a little structure to help the posting start, and to let you guys know what to expect. Please feel free to reply to any posts and leave feedback. I’d love for discussion to start regarding any posts, and feedback is always welcome!