Transcript from Interview
Why Data Science as a career?
It's a really fascinating area where you can see a lot of impact from your work. It's a fairly new field as well, because we only now have both the computing power and the understanding that much may be obtained from data. So, it's an area with a huge amount of potential for taking all that data that companies have been collecting for decades (and not knowing what to do with it) - and going a step above to get a lot of power out of the data.
What have you been up to at CBRE?
*Short answer: Lots of proprietary projects.*
We couldn't publish Quentin's answers, unfortunately, but he is working on a lot of interesting/amazing/innovative things!
He did write a great, open-source library called Manatee.
What characteristics do you look for in a data scientist?
Diplomacy, curiosity, and communication. You've got to understand how things fit together, and that's not always easy.
You've got to have technical expertise in areas like machine learning algorithms - and then you need to be able to communicate what your models are telling you to non-technical users. Knowing everything in theory, but not having a background in applying concepts in practice, won't work.
What blogs, websites, books, etc. have helped you in learning about this field?
I follow an immense amount of people on Twitter. There are a lot of great people who teach and speak about data science concepts. Now, there is a lot of stuff to filter out, like, "How to Become a Data Scientist in 5 Easy Steps."
I haven't found a great book yet, but I just bought a book by Sebastian Raschka. He's definitely someone to follow.
What tools or languages are you excited about?
You occasionally see in data science: Python vs. R. I think those who are using data science in production are often using Python. R has a number of great tools, but they are just not (yet) production stable. In Python, scikit-learn is essential. Also, pandas, of course. I've also started working with PySpark. What I really want to look into is Dask and Blaze.
What conferences/meetups/etc. have been really helpful?
I go to a meetup in Vancouver which is called the Data Science Advanced Journal Club. Every two weeks, we pick a paper to read. Then we discuss it. It's very good and cutting edge.
I also participate in Kaggle competitions. In the meetups around the Kaggle competitions, we read up on what people have done, and we try to do them ourselves. The last one I went to, I spoke for about two hours about a solution I submitted. In terms of that competition, I am the 21st.
What do you like to do outside of work?
Most of the time, I get home from work, and I sit on the balcony and read. The weather is beautiful, and I have a great series of books.
Otherwise, I like the odd computer game and going out with friends. Also, I love having good beer.