Can you start by introducing yourself?
My name is Felipe Inostroza, I studied Civil Industrial Engineering at Universidad Técnica Federico Santa Maria, in Chile. After finishing my bachelor's in engineering, I had the opportunity to make a Master In Management – Engineering, in France. My areas of expertise were operation management and risk management.
Before Le Wagon, I was finishing my thesis which was based on a math solution. With this final study project, I realized that I really liked using math to solve real problems, and it was very cool modeling solutions. I mean, in the end, you just put some inputs and voilà you have your solution ready to use 🙌🏼.
Why learn Data Science at Le Wagon?
During my master, I took a major specialization in Digital Business and ITs, which covered parts of digital transformation but at a strategic level. I realized I was very interested in this tech field, particularly in the data one. In this major, there was a complete course of data analysis taught by Le Wagon, and there I discovered the cool methodology of Le Wagon.
I remember investigating the programs Le Wagon offered and I realized they were launching their first data science bootcamp. The full-time program seduced me from the beginning because it takes only 9 weeks to achieve. I just had finished my studies, it looked like an effective way to learn skills allowing me to start a professional career in a field I really like, and that in a very short time.
How did your 9 weeks of bootcamp go?
On my first day at Le Wagon I was in shock, it was my first time dealing with all the programming tools and interfaces needed to make coding projects. Everything was totally new to me.
However, it wasn’t too difficult because, since day one, there was always a teacher available to answer my questions. During the first week, it was a bit difficult to formulate a question using the same technical language, but after a while, I learned it because it became everyday bread.
I felt very comfortable with Le Wagon's teaching methodology. The lectures were so clear, the teachers were people really prepared for the topics, and the environment built with my classmates was very productive and friendly. This collaborative environment was the best to learn data science in.
With my background, it wasn’t too hard familiarizing myself with data science concepts, however, I learned MANY new concepts and I didn't believe it would actually be possible to learn so much in 9 weeks.
What have you been doing since graduating?
Since graduating from the Data Science Bootcamp at Le Wagon in 2020, I came back to Chile looking for opportunities in positions related to data. The data field is growing in Chile, and every day, there are more and more job offers for tech professionals. Unfortunately, there are few organizations willing to train talents, and most of them are looking for high seniority levels.
During my job search, I worked as a teacher at Le Wagon Argentina and Brasil, and that was cool because it helped me strengthen every topic learned during the bootcamp, and getting better at interviews as well.
After some interviews with startups and companies, I was interested in, I got hired by LATAM Airlines as a Data Scientist.
What does your job consist of?
Currently, I work as a Data Scientist at LATAM Airlines, which is the most important Airline in South America. I am working in the Advanced Analytics area, and we are the area in charge of making LATAM Airlines a data-driven company by building technological solutions for every department and thus, adding value to the firm.
We are a big team with different seniority levels, and every time I need help with something, there is someone to help me.
My role consists of working with the fuel department and developing new data products together, following the objectives that the company draws. I am responsible for fuel data products, and I handle different tasks, from management ones: defining backlog, building milestones, creating roadmaps, and negotiating with my product owner; to more technical ones: data analysis, model assessment, feature engineering, and storytelling.
So far, it's been great! It is a pleasure to be part of a company that invests many resources in the tech area. And one of my favorite parts is that, once a week, we get time to study any topic that we want to deepen so we can keep growing and upskilling.
Any advice for anyone thinking of learning data science?
There are two challenges in the data science path, coding and mathematics.
Focus on understanding the math concepts well: why you are using one model and not another one, what kind of problem you are trying to solve. Also cover statistic concepts. This is the most important part.
In relation to the programming part, just be open to learning new things every day, and be aware that, it’s not about memorizing things, it’s just about getting the general idea of programming and understand the way of coding, after that you can google all your doubts. In the end, Google and Stackoverflow will be your best friend.