What's your background?
I am from Brazil, and I'm a statistician and an economist. I work at Hotmart, which is an online platform that helps producers of digital goods to find affiliates and sell digital products, like online courses, ebooks, and webinars. I am the manager of the business intelligence and analytics team. We call it "business intelligence and analytics," but most of our job is data science and dealing with big data. We are responsible for the fingerprint of our shoppers and affiliates. This is big data—we need a lot of clusters running all the time because we are dealing with millions and millions of datapoints. We conduct studies for the company to avoid fraud, to discover what we can do to convert better. We help make data-driven decisions for the whole company.
In Brazil, we have university that teaches statistics, just statistics. A kind of four year program in statistics, and the same for economics, a four your program in economics. So I have two majors.
Since I was very young, I discovered I loved numbers. Every time I went to a bus stop, my friends would say "oh, man, I've been waiting for 50 minutes today." But I knew that wasn't accurate. Every day I see a lot of people who can't understand probabilities. I decided to study more and I liked it, so I started my program in statistics. But I didn't like it too much because the courses were very theoretical. It was a lot of theory all the time and I couldn't see it in practice. I studied statistical inference. Today I see how it is important, but when I was a student, I would say "probability… I know probability. Why do I need to study inference? Why do I need to study millions of different distributions? Why do I need to prove it so formally?" So I wasn't happy with my courses. At the same time, I started studying economics. So in the morning I studied statistics, and at night I studied economics, and then I started working in the afternoon. So I started to put the theories into practice. And when I started putting it into practice, I discovered I loved statistics.
When did you first consider yourself a "data scientist"?
Four years ago, I decided that I needed to create a career plan for myself, but I had never heard of data science. I knew I wanted to be a specialist in information. So I knew I wanted to collect data, prepare data, and analyze data. Today I know that maybe the most important part is also to present it. The first time that I saw myself as a data scientist was when I would started writing "specialist in information" on my resume.
What is the data science landscape like in Brazil?
Data science is growing fast in Brazil. Companies are starting to build data science teams. For example, a big telecom company is trying to build a team of 100 data scientists. It is hard to find data scientists in Brazil. I spent four months to find the last data scientist I hired. A lot of people from computer science are trying to be data scientists, and some people from statistics are trying to become data scientists. Udacity opened an office in Brazil, and they are growing very fast in Brazil. It is a market that will grow more and more.
What do you like about DataCamp?
On DataCamp, we have a lot of practice. This is a very good part of the platform. We study, then try. Study, then try. That is very good.
I liked that it was easy to practice data science. You don't need to install Python on your machine, you don't have to set up a server or something like that. I like the way that you film your videos. You have some very good teachers. I am a fan of Hugo—he is kind of a data science lumberjack. I really like the courses. For me, it was easy to start to understand Python and some libraries. The libraries you teach in your courses are the best. Numpy, bokeh, scikit-learn, scipy.
What types of skills have you learned on DataCamp?
Data visualization skills with bokeh. I discovered SQLalchemy, I had never heard of it before. I tried to figure out on Google, do I need it? I used to make a lot of queries in SQL, so I thought, I know how to do it, I don't need to learn it again. But after understanding it better, I think it is important—I like SQLalchemy.
Are you able to use these skills at your job?
Oh yeah. I use a lot of them. Today I am more a manager than an analyst. It is a paradox for me: I want to analyze data in part of my time, I don't want to just manage and do administrative things. As a manager, for me, it helps to show my team new packages, new ways to solve problems, like data visualization techniques, and some problems we solved with random forests, which I learned on DataCamp.
What are some of the exciting projects you've worked on?
We made a fraud detection algorithm, which was very nice. We had a project where we were clustering clients. Customer clustering, segmentation, things like that. We made some classification models.
Advice to newcomers?
Try to practice and study. It is important to practice. To try to study a few minutes every day. I think it is better than three hours one day, then going a week without studying. A few minutes a day works better for me.
What is the biggest challenge you are currently facing?
The most important challenge for me is to talk to business people using statistics. When you talk to a lot of data science people with statistics, they understand everything. When you need to talk with people who are making the decisions, on the other side of the company, you need to improve a lot of skills that are not R, not Python, not statistics. A lot of data visualization, but it is communication, it is to make the data simple. For me, it is the most important challenge.
Greatest benefit of learning with DataCamp?
You are a curator of libraries and packages and models and knowledge. I don't need to read 10, 30 articles to decide this is garbage, this is good. You already filter it for me. I can spend my time on important things. That is the best part, you are the curator. When everything is curated for you, you spend less time on unimportant things and can learn faster.