Apply now

Landing an internship in data science at one of the fastest growing startups while pursuing my Business Degree.

I am a business student currently pursuing a double degree from HEC Paris in France and Yale University. I just started a gap year which I want to dedicate to developing technical skills. I enrolled in Le Wagon’s Data Science bootcamp in Berlin and am now excited to soon start a data science internship at a Proptech start-up in Paris called Hosman.

Landing an internship in data science at one of the fastest growing startups while pursuing my Business Degree.
Featuring graduate Anton Barthelmess More about Anton
Share article
My name is Anton, I am half French and half German. I am a business student currently pursuing a double degree from HEC Paris in France and Yale University in the US. In between the two degrees I had the opportunity to take two gap years. I used the first gap year to do internships with a fintech startup and in strategy consulting. I just started the second gap year which I want to dedicate to developing technical skills. I therefore enrolled in Le Wagon’s Data Science bootcamp in Berlin. Building upon the bootcamp that I just completed, I am now excited to soon start a data science internship at a Proptech start-up in Paris called Hosman. I think this will be a great opportunity to review and apply all the concepts learned using real use cases and data.

I did not have knowledge about data science prior to the bootcamp. However I completed Le Wagon’s web development bootcamp two and a half years ago, so programming was not new to me. After the first bootcamp, I regularly coded on a side-project with which I applied to Station F (an incubator in Paris). However, following my rejection from Station F, I halted the project and embarked on internships instead. The internships did not involve coding and thus took a long-term break from coding. Nevertheless, I did not forget the logic of coding and since Ruby (the language taught in the web dev bootcamp) is quite similar to Python - it was easier to get up to speed at the beginning of the bootcamp.

 From the beginning, I was determined to do an internship in data science after the bootcamp as I knew that Le Wagon would give a solid foundation and overview of many concepts (...)

I expected to get a solid foundation in the most important concepts of data science when joining the Data Science Bootcamp. To be honest, when I started the bootcamp I was not exactly sure what that meant but I trusted Le Wagon’s curriculum and the many positive reviews of it. From the beginning, I was determined to do an internship in data science after the bootcamp as I knew that Le Wagon would give a solid foundation and overview of many concepts but that without concrete application it would quickly fade away and be forgotten. 

Long-term, I will most probably work in a business-related field but I want to be able to easily add data science insights to my work. Moreover, I am also planning on working on many data related side projects with the hope of maybe one day launching my own business.
Anton presenting during the demo day
One thing that really stood out during my experience at Le Wagon was the diversity of the people in the batch. Despite only being 28 students there was a huge variety in terms of backgrounds and nationalities with people coming from all walks of life. This was quite a change from what I am used to at business school where most students have similar backgrounds and aspirations. As such, the bootcamp did not only allow me to learn a lot technically, but it was also a unique opportunity to meet new and interesting people that I otherwise would not have met.

(...) there was a huge variety in terms of backgrounds and nationalities with people coming from all walks of life. This was quite a change from what I am used to at business school where most students have similar backgrounds and aspirations.

The other thing that stood out to me was the very positive general “vibe” of the bootcamp. Despite the Covid situation, friendliness, willingness to help others and general enthusiasm for the powerful concepts that we were learning characterized the atmosphere. I think places where you learn so much at such a fast pace are often fueled by a sort of underlying competition and pressure to perform. This was not the case at Le Wagon at all. Learning in such a laid back and friendly yet “productive” environment alongside interesting people really was an awesome and unique experience.

What pushed me to staying productive during the bootcamp was being part of a community which shares a common goal of learning as much as possible about data science in a short period of time was a great motivation boost. For example, when running frustrated because your code didn’t work there was always someone ready to do a mini-break with you. Those little social moments often helped to put the frustration behind and get back to your code with new motivation being ready to fix it. Finally, knowing that a data science internship awaited me directly after the bootcamp forced me to stay motivated and focused throughout the course as I knew that I will need all of that knowledge later on.

The other thing that stood out to me was the very positive general “vibe” of the bootcamp. Despite the Covid situation, friendliness, willingness to help others and general enthusiasm for the powerful concepts that we were learning characterized the atmosphere.

My final project during the last two weeks of the bootcamp focused on leveraging NLP techniques (Neuro Linguistic Programming) in order to get more information about news articles. I am a passionate news reader and generally also very interested in the news sector from a business point of view. I was thus keen on applying data science techniques to news to extract more insights. With our team we built two algorithms: a text summarization algorithm, summarizing a news article in a few bullet points and a sentiment analysis algorithm for the related reader comments to understand if readers are reacting positively or negatively to the article. We then built a very nice and user-friendly web app to allow users to use our algorithms by simply copy/pasting the link of their chosen article into our tool. Our team was great and I am very satisfied with what we achieved. It was awesome to apply these incredibly powerful data science techniques to a subject that really interests me. Last but not least, pitching the project to the rest of the cohort on the last day, after two weeks of hard work, was a festive and rewarding moment for everyone and a great way to conclude the bootcamp.

I just completed the data science bootcamp in Berlin as I write this. I am currently reviewing the most important topics of the course by re-watching some of the lectures (they are all recorded) and taking notes. During the bootcamp we covered many topics. With each day comes a new topic and therefore you might have the impression that often the things you learned only a few days earlier were already forgotten by your brain to make space for the new things that you were then learning. However, fortunately when reviewing the different topics in my own time, things came back quickly and stayed in my head. I therefore think it is important to keep some time free after the bootcamp to review all the concepts.
Anton during the bootcamp in Berlin
The next step for me is doing an internship in a real estate start-up in Paris called Hosman. My internship will be very hands-on and cover data analysis and data science tasks. I thus expect it to be a great learning experience to build on what we learned at Le Wagon.

I found my internship quite quickly. In fact, I applied for internships when we were halfway through the bootcamp. It was challenging to interview and prepare for technical questions while coping with the pace of the bootcamp. I probably would not advise doing it, unless you are time constrained like I was (I had to start the internship shortly after the bootcamp ended). Nevertheless, the interviews went well and I secured my position ten days after sending out my application. The fact that Hosman’s founder also did Le Wagon in the past (web dev course) helped as he was familiar with how the bootcamp was structured.

One piece of advice I’d give to anyone thinking about starting the bootcamp is to have an idea of how you want to apply the things learned during the bootcamp after it’s done. Learning how to code is similar to learning a new language.

During the internship, I will be the one responsible for getting information from the company’s database, doing analyses and then presenting them via diverse visualization tools (data analysis part). I will also have discussions with the CTO to see what machine learning algorithms we could develop to support the business (data science part).

Until I start, I am reviewing the most important lectures and exercises of the bootcamp via Kitt, Le Wagon’s learning platform, which is super handy and to which you have life-long access.

One piece of advice I’d give to anyone thinking about starting the bootcamp is to have an idea of how you want to apply the things learned during the bootcamp after it’s done. Learning how to code is similar to learning a new language. Le Wagon gives you a solid foundation but if you do not apply it concretely and practice it after the bootcamp you will forget many things very fast. As such if you are not planning on pursuing a career in data after the bootcamp, I would strongly advise to work on personal projects or do an internship in data. 

Finally, I think it is most important that you are motivated and self-confident in your capacity to learn. The rest will follow - and as we were wisely told on the first day of the bootcamp: “just trust the process”.

More resources:

Want to know more about Le Wagon's bootcamps?
Go further illustration

Are you ready to learn coding?

We are in 43 cities worldwide.

Laptop illustration