Graduates | Le Wagon

See the great roles Le Wagon alumni have found

Phillip Zastrow

Data Analyst
Smart Pricer

From Project Manager to Data Analyst (and Teacher at Le Wagon!)

Phillip Zastrow

Data Analyst
Smart Pricer

Hello Phillip! Can you introduce yourself?

Sure. I'm Phillip, 33 years old and I come from Germany. In the past I have lived in Valencia, Aarhus, but mostly in Berlin. Last year I decided to join Le Wagon's Data Science bootcamp in batch #469.

What did you do before joining Le Wagon in Lisbon?

Before Le Wagon, I studied Mechanical Engineering at Berlin Technical University with a focus on Entrepreneurship and Climate Change. Afterwards, I worked as Project Manager/Structural Engineer for four years at WINDnovation, a wind energy company.

During this time, I became more and more unhappy with my scope of work and felt a bit stuck. My work got rather repetitive and if it wasn't for my great colleagues, I would have probably left earlier.

How did you come up with the idea of a Data Science bootcamp?

I often had the idea of getting into coding, but it always felt like a big obstacle. Anyway, I talked to some friends who had a major career change after attending a bootcamp and then did some research myself.

I found out that there are three major paths: Web Dev, Data Science and Data Analytics. Web Development seemed a little too far away from my engineering background, and when I heard that Data Science still covers Analytics to some extent, my decision was made. Back then I did not really know what to expect from Data Science, but I was willing to find out!

First, I was looking for a bootcamp that could fit my schedule, then I read several online reviews and decided to go for Le Wagon in Lisbon. Not the most romantic story of how I got here, but I am absolutely happy with the choice I made!

Cool! And how was your bootcamp experience?

Intense but so rewarding. I liked the combination of fast-paced learning and community feeling. People have been supportive throughout the bootcamp and this keeps you motivated, even through more complicated lectures!

Also, I enjoyed having a fresh topic every day, I liked that you always had something new to work on.

What did you learn from your experience at Le Wagon?

The first of two most important things I learnt is to understand how to fix/debug/solve issues along the route. It is incredibly important to be able to get yourself out of a hole and I believe this was taught us really well. The second thing is… Pandas. It is an amazing library and completely changed my opinion on Excel!

And what was your biggest challenge during the bootcamp?

Definitely the Data Engineering part. Coding is one thing, but these infrastructure topics are an entirely new field where you really have to work yourself into. Honestly, this is where I struggled the most and it took me a while to understand.

Your best moment at Le Wagon?

Definitely Demo Day. Everything you have done, and especially the two project weeks, build up to this moment where you finally present your own first working code product! It's so great to see the final result of your efforts.

Phillip presenting 'Fed up!', his team's final project

As you said, Le Wagon is all about community. How do you relate to this network?

I try to help people as much as I can. I participated in alumni panels to share my experience with new potential students and I am always happy to help. I also try to stay in touch with my fellow bootcampers!

Great. And now you found a job as a Data Analyst and became TA at Le Wagon, congratulations! Can you tell us more about it?

Yeah, that's true. I am now working at Smart Pricer as Data Analyst/IT Project Manager. Many things I learnt during the bootcamp actually helped me get this job and gave me the ability to start performing early on. In particular, knowing how to clean, manipulate, complete and ultimately visualize and interpret big data sets gave me a real advantage. On top of that, I am slowly getting into the Data Science topics at work, where my brief xgboost and fbprophet will likely come in hand. I am still in the onboarding phase but I love that there is so much more to learn!

Apart from that, I am very happy to get the chance to come back to Le Wagon, now as a Teaching Assistant. I am really excited to strengthen my competences in the field and learn how to best explain concepts. I'd say it is a real win-win situation where I get to help enthusiastic students while improving new skills!

Thank you for sharing your story, Phillip! Any tips for those thinking about a Data Science bootcamp?

A bootcamp at Le Wagon is definitely worth it. It is 9 weeks of hard work and dedication and you will see what incredible things can be accomplished in such a short amount of time! Coding seemed complicated to me and I was always hesitant to get into it, but it's not! Just go for it.

One more important thing: do not give up in the process. There will definitely be situations where you think you will not get there...Stick with it and trust the moment. If the motivation is there, you will get through it!

Samuel Rasetti

Data Analyst

Becoming a data analyst: Samuel's inspiring journey

Samuel Rasetti

Data Analyst

Why did you decide to change careers?

I've always had digital-related jobs in different companies. Among others, I worked 8 years in customer support, but it wasn’t a field where I wanted to evolve.

I wanted to transition into a technical profession in data science. I got interested in this field for personal taste and because it’s a highly in-demand sector in Montreal. So I started taking online courses to learn Python and data basics.

How did you hear about Le Wagon?

I met Antoine, the co-founder of Le Wagon Montréal, during a Hackernest event. He talked about bootcamps and Le Wagon's philosophy... I was hooked!

I started attending Le Wagon Talk, a series of events to meet Montreal tech entrepreneurs and some workshops. I got to know the staff very well. I even was the first participant in the info sessions!

I really liked Le Wagon brand. It's not only a bootcamp but a community that is truly connected to the tech ecosystem.

The team organizes free workshops all year long and this shows that they take knowledge transmission to heart. I liked these values and when the data science bootcamp was launched, I didn’t hesitate to join the first batch.

What did you think of your bootcamp experience?

I really enjoyed the bootcamp because I was able to explore all aspects of data science, from collecting data to putting machine learning models into production. I also learned about jobs that I didn't know about - for example, I realized that I love data engineering.

I found it was stimulating to be challenged every day and to progress in complex areas.

It’s very satisfying to get results when learning concepts like deep learning, natural language processing, or image recognition. And finally, you realize that artificial intelligence and machine learning are mostly about probability and statistics!

How did your job search go after the bootcamp?

I realized that data analyst positions were an excellent gateway to set foot in the industry and later move on to other positions like data engineer.

Since Le Wagon gave me a solid ground to build on, I continued to expand my knowledge, especially in business intelligence, SQL, and back-end development with Python. Then, I worked on personal projects to add to my portfolio. This helped me a lot with the technical interviews!

Recruiters appreciated that I chose to put myself at risk and invest my time and money in a bootcamp to learn brand new concepts. They understood that I was highly motivated and that I put a lot of effort into getting there.

What’s your role at Ludia?

Ludia is a Canadian mobile game development company. I started working with them as a Business Analysis intern.

Today I’m a data analyst working on a specific game. When the development team launches new features or updates, I'm in charge of measuring its impact on players. For example, we look at the effect on players’ retention and behavior, or whether a new feature has generated more revenue.

For this, I mainly use SQL to analyze the data and Tableau for visualization.

How do you use the skills you learned at Le Wagon

The strength of Le Wagon’s program is that you learn how to search for information and it's vital to be autonomous in this job.

We’re always encouraged to cultivate curiosity, research, and learning. It's a mindset that I kept after the bootcamp.

I also learned how to collaborate in a team and use tools like Github and Slack, which are very useful in my job today.

Any advice for people who want to get into data science?

Start simple and experiment with small projects. Even a simple "hello world" can be a win! You have to challenge yourself to succeed in this field.

If you want to go further, Le Wagon is a great accelerator and an excellent first step to get into data science. After that, you have to keep learning to prove yourself!

Congratulations Samuel! We wish you the best in this exciting journey :)

Brieuc Boonen

Data Scientist
Agilytic

From mechanical engineering studies to data science: the journey of Brieuc

Brieuc Boonen

Data Scientist
Agilytic

My name is Brieuc Boonen. I studied mechanical engineering at UCL, in Belgium. After submitting my thesis, in which I had to process a tremendous amount of data, I realised that I had very little experience in this field (Matlab was cool, but Python looked even cooler 😎). This made me want to learn more about this topic and attending a Data Science bootcamp seemed to be a great opportunity to deepen my knowledge.

What did you like about the bootcamp?

It was a great experience! Even with a technical academic background, I learned new concepts that I was not familiar with.

The greatest added value of Le Wagon is the presence of competent teachers, available at all times to answer questions, and to bring their expertise to best tackle "code challenges".

I really enjoyed the roadmap, which aims to discover all the principles that drive data science.

What is your role now?

Since finishing the Data Science Bootcamp at Le Wagon in 2020, I've been working as a Data Scientist at Agilytic. We are a growing consultancy firm helping companies across many industries (such as banking, insurance, telecommunications, healthcare, pharmaceuticals, automotive, and more) to achieve their goals through the smarter use of data.

I really like my experience in this role. Since day one, I have acquired a certain level of responsibility and ownership. In fact, I am responsible for every project I’m part of, from data analytics and modeling to data storytelling and providing recommendations. If I need help, a Senior Data Scientist is always there to offer guidance. In my spare time, I also can study various certifications to continue expanding my knowledge and improve my skills.

So far, I have already established a segmentation, a dispatching algorithm, developed a web app interface using Flask and passed my first certification: Power BI. Next up between two projects, I look forward to acquiring both DataBricks and AWS Cloud Practioner certifications.

If you're interested in data science or data engineering, Agilytic is hiring! Check out www.agilytic.be/careers

How did your job search go after graduating from Le Wagon?

The IA/Data Science field is still relatively new in Belgium, in particular in Brussels. I discovered this opportunity, mainly through word of mouth, but also via social networks, thanks to the BestRegards podcasts (co-created by our Data Science alumni, Joanna Vitiello). I had four interviews, one of which was purely technical. Fortunately, Le Wagon gave me confidence in my Python programming skills to succeed.

A piece of advice for people looking to start their journey in Data Science?

1. Take the time to learn all the mathematical and programming concepts behind it. Once you have the fundamentals down, it is much easier to add an extra layer of knowledge.

2.Data science allows you to exploit data from top to bottom. You can easily get lost. It's your job to stay focused on the objectives and build a story around the data. In fact, this is almost the most difficult thing in the field 😉

Enjoy!

Aishwarya Wahane

Data Scientist
Virtusize

From antennas to data science: the story of Aishu

Aishwarya Wahane

Data Scientist
Virtusize

Hello, Aishu! How did your interest in Data Science evolve?

After finishing my undergraduate degree in electronics engineering, I realised I loved research and wanted to push it further. I started my career in academia, with a focus on satellite and wireless communications since I truly loved working with antennas and tracking satellites. At the same time, a friend introduced me to programming and I became fascinated by what a few lines could do.

When my family moved to Japan, I landed an internship at a software company and learned Python. This ended up being a great stepping stone for a career in data science. I realized that I really enjoyed going from messy data to clean insights and finding patterns to make better decisions.

Long story short, I attended a Le Wagon workshop for data analytics and really enjoyed Trouni’s (one of our Lead Teachers) teaching style. When I learned that a full Data Science bootcamp would be taught the next semester, I immediately decided to apply.

What did you like about the bootcamp?

The whole curriculum was challenging and well-organized. Learning all of that stuff laid a solid groundwork not only for my graduation project but also for all my personal projects afterwards.

I particularly loved the data analytics module. Never having learned statistics before and discovering some patterns in data was a blast.

It was sometimes challenging for me to understand the theoretical part of some machine learning models like linear regression, but Le Wagon teachers managed to break down the subject in a very nice and clear way. The greatest thing about the bootcamp is that even the most difficult technical knowledge can be taught to people coming from non-math backgrounds like me.

What did you do for your final project?

Together with my teammates Arron and Njeri, we worked on an application that could split any song into different musical instruments. At first, we researched models that could be a good case for separating tracks, and after that we split up roles to speed up the development process. I was working on the front end (using Streamlit) and some back-end on limited parts. I am quite proud of our pitch during Demo Day, and I am pretty sure it caught some people’s attention!

What did you do after graduation?

After the bootcamp, I started working on a personal project with a goal to predict poverty. I was inspired by a few Stanford students who wanted to use satellite images to map poor regions. It helped me realize that my passion lies in working with meaningful projects and I started to apply for jobs with that in mind.

Eventually, I received two job offers and accepted a junior data scientist position from Virtusize, my current employer. As a shopaholic, I am very familiar with the frustration of buying clothes that do not fit and having to return them. Virtusize solves this problem by developing a virtual fitting solution that enables online fashion retailers to illustrate size and fit for consumers. I am very excited about the product and will work doubly hard to help Virtusize become the standard solution for size and fit in the Asian online fashion industry and beyond.

Over 50% of our company are women. Let me tell you more: the whole data science team are women! I’m proud to work in a supportive environment where everyone is encouraged to pursue their passions regardless of gender and background.

Sounds amazing! Thanks for the talk, Aishu. Wishing you all the best in your career journey.

Mariam Ammar

Data Analyst
31TEN

Mariam: Transition from A Teacher to A Data Analyst

Mariam Ammar

Data Analyst
31TEN

What were you doing before you join Le Wagon? What makes you switch to a data career?

Consider What You Want

I have my bachelor's degree in Art and master's in Economics. When I first came to Shanghai, I was working at a bilingual school and tutoring on the side. Working in Education in China has a lot of benefits, but I found that I was no longer feeling challenged after all the excitement that came from traveling and taking holidays wore off.

After a while, I would start to ask myself what I really wanted to do long-term. "Do I want to become a teacher? If i want to be a teacher, then need to take it more seriously and become certificated". I realized that I wanted to pursue a different path and I started to search for economics related positions. To be honest, I had little idea of what I really wanted to do and "data science" appeared many times in my searches. I started to learn about this new field and decided that this was the one I wanted to commit to.

Why chose Le Wagon?

Coding Workout with Classmates at Le Wagon

I believe different people join for different reasons. Some people join because they want to work better with their data team at their own company. I participated in the bootcamp as a step to build my career in data science.

Data Science Bootcamp in Shanghai provides a good community learning after COVID Hits. After COVID, many US university courses took place online however here in Shanghai Le Wagon was able to hold onsite classes. Like working out, you are going to exert yourself a lot more when you are doing it with a group of people onsite than you would if you were alone. Also you get the support and help from instructors and classmates.

Marriam's Data Science classroom at Le Wagon, with instructor Pavel and classmates

How was the experience at Le Wagon? Was the bootcamp intense and difficult for you?

Have A Growth Mindset

It depends on how difficult and intense you want to make it. I was honest to myself and knew my weaknesses and strengths. Coming from a non-technical background, nobody can be a data scientist in just two months. Instead of aiming to grasp every detail of the courses, I made sure I understood the fundamental concepts so that I could revisit the content that interested me and dive deeper later on.

Having a growth mindset is very important. Everybody in the classroom came from a varied level of the tech background. It is hard to do sometimes, but you should always focus on how you improve personally instead of comparing yourself with others. Coding and math may seem intimidating at first but with enough time and effort anyone can become a key player. The program also gives a good overview of data science, a quite complex and dynamic field.

What position are you doing right now?

I work as data analysis manager for digital agency 31Ten . My job focuses on developing our data departments and providing data science solutions for our clients to grow their business successfully.

Foreign companies are mesmerized by the diverse digital ecosystem that China has to offer. They are interested in creating WeChat Mini Programs and came to us to help them get on the local platform to enter the chinese market. We also do social media marketing for them. The chinese market is quite competitive. You have a lot of talent working around the clock and adapting quickly to the changed. In tech, and particularly here in China, you need to always be learning. Most of the foreign companies have to change their entire strategy to set up.

How did you find the job, was it smooth to get into the China tech world as a foreigner?

Le Wagon's Connection Is Powerful

It is hard even if you are a local. It's about putting effort in including going to network events, making yourself visible in groups, communities. Le Wagon provides me with very good connections. When I went to interviews, most of the interviewers knew about what Le Wagon was or had a direct connection with one of the instructors. Le Wagon certainly has a name in the tech industry here in Shanghai.

How was your transition to the data world? Was it a big step?

Nothing That Is Worth Doing Comes Easy

Of course. Now, I hold a lot more responsibility than the teaching job because most of our clients are big international companies from different industries. My first major project was creating data literacy course for a major fashion luxury brand. There was a very steep learning curve. However, it is rewarding because I learned a lot, not only about data but also about other fields and industries.

Nothing that is worth doing is easy. You have to be proactive, put yourself out there, be okay about struggling and working hard. It is also about managing your expectations because it is simply not possible to become a developer or data scientist in a couple of months. To make full use of Le Wagon, you need to see it as a starting point that can propel you towards your new journey.

Want to know more about the Data Science Bootcamp?

Now we have both full-time and part-time options here in Shanghai

Click the link below to download the syllabus or directly sign up for the course.

10% early bird discount available until April 2nd, 2021!

https://www.lewagon.com/shanghai/data-science-course/full-time

https://www.lewagon.com/shanghai/data-science-course/part-time

More questions about our programs? Contact our admission manager Cheng for more information:

Arron Ritchie

Data Scientist
Hacarus

Alumni story: Arron, musician and recruiter turned Data Scientist

Arron Ritchie

Data Scientist
Hacarus

Hi, Arron! Thanks for your time. What were you doing before joining Le Wagon Tokyo?

When I was a kid, I learned basic programming to make terrible games (laugh) but eventually my interest in music outweighed it. It could be just my assumption, but I feel that musicians tend to have a natural intuition towards programming or any other written language. There's actually a lot of musicians at my current company!

At university, I studied guitar and afterwards worked as a musician on cruise ships floating around the world. My growing interest in Asia brought me to Japan where I found a job as a tech recruiter for data science positions. Chatting with data scientists and product managers from firms at the forefront of technology sparked my interest in tech again.

I started learning Python online, but it was hard to filter through all the info out there and identify the core skill set I would need for a career transition. I decided to search for on-campus courses with teacher support, and that’s when I found Le Wagon.

How was your Data Science bootcamp experience?

Le Wagon Data Science bootcamp was definitely a great challenge! I really appreciated all the support throughout the course, and a really good approach on how to help students go through the tasks. Instead of offering us a solution on a platter, all teachers were great and gave us the capability to solve challenges by ourselves - that’s actually what I needed. In the development world, your code often crashes and now I have no problem scrolling through errors and looking for the correct solution.

One of my favorite modules so far was Deep Learning. It was fascinating to see how deep learning solves problems differently compared to the more traditional scikit-learn methods, and how much flexibility you can get out of models. Our Deep Learning teacher Yann literally infected anyone with his enthusiasm and passion!

Arron won Codewars challenges between Data Science students

Sounds cool! What were you working on for Project Weeks?

I pitched my idea of solving an issue for musicians learning a new track and had two batchmates joining me. The goal was to run a song through a Deep Learning model and had it split into separate musical instruments. With the help of Aishu and Njeri, we came up with a solid-looking product that had a wow effect during our Demo Day presentation.

It was really important to see other people's approaches and get a better understanding of how to have a business impact as a data scientist. Many people optimize algorithms and solve obscure problems on an academic level, whereas the bootcamp focuses on applying Data Science knowledge to real world problems with an actual impact.

Watch Arron pitching at the Demo Day (from 21:15)

Do you think that math knowledge is crucial for Data Scientists?

Lots of people have the impression that data science requires a math background - that’s not true! My background is light years away from STEM. Of course, having some competency or at least the willingness to learn statistics and inference is needed to pick things up. But you are not expected to be a math wizard to become a data scientist unless you want to go into academia or work at the R&D department of a firm tweaking hyper parameters and building new architectures for models. The majority of data scientists are using already predetermined architecture.

What did you do after graduating from Le Wagon?

After graduation from Le Wagon Data Science bootcamp, I spent one week before Christmas holidays sending out as many applications as possible. When January came, I went through my emails and a few people had reached out to me already. It took me just 2,5 weeks after graduation to get a job offer from Hacarus, a Kyoto-based AI startup that just opened up a new office in Tokyo.

Hacarus has a very interesting approach: it focuses on an explainable AI using sparse modeling and machine learning methods that can be visualized so that the end users can actually see what it's happening. In addition, the company has a really nice atmosphere, which was very important for me coming from a very high-stress environment. People here deliver great results because they like the products they’re working on, rather than have a supervisor breathing down their neck.

What are you working on right now?

I'm working on a computer vision task building and reconstructing different modules in PyTorch. It comes with an additional issue of how to effectively annotate and pre-process images to help model learn the features of the problem.

Hacarus is a really enticing environment and a great place to learn new skills. We've got 15 or 16 people on the data science team, which means a lot of people to reach out to and learn from.

Do you think it is difficult to get a Data Scientist job in Japan now?

Data Science and Data Analytics are the fastest-growing sectors for talent demand, and Japan has one of the most candidate short markets in the world. If you speak Japanese and English and you have a basic data science skill set, you will be literally hunted down by recruiters! I don't speak much Japanese yet I managed to land a Data Science job 2.5 weeks only after starting my job search. Keep digging, actively reach out to recruiters and hiring companies - and you will definitely find a great place to work.

Thank you so much, Arron! Wishing you all the best in your new career journey.