Traineeship Data Science with Erik

Hello, I’m Erik, I work at CB as a member of a data science team who work towards predicting the future. I focus on Natural Language Processing and make data-driven predictions on a product’s pre-destined performance in the market. When I am not predicting the future, I am growing it: cultivating oyster mushrooms from coffee grounds at my urban farm, Fungi Factory.

My studies specialized in sustainable business models and innovation, and I was approached by Young Mavericks in the finale stage of my master’s programme. I finished my Master’s degree at KLM, where we analyzed total ticket sales. I found that playing with large amounts of data, getting them to answer the right questions, was fun and interesting, so from there I took the course Data Learning.

Starting at Young Mavericks

I came to Young Mavericks with a keen interest in data, I was considering a traineeship and I was sold after I considering the benefits of joining a start-up with young energetic talent. I learned a lot from the training courses. The sessions were a great introduction to machine learning and helped me gain extensive insight into the various machine learning tools and processes. In addition, I learned a lot about dealing with and tackling specific problems that can arise during a project.

Working at the partner

I was a little nervous for my interview at CB, but I was pleasantly surprised by how smoothly the conversation went. I started at CB in a data science team where we were given a lot of freedom and space to discover what we could do for certain CB data. Our first assignment gave us three months to demonstrate what we could do with the data. We have already accomplished various assignments as a team. One example had us building a keyword generator that could automatically identify keywords to describe the book mined from its digital content.

The value of Young Mavericks’ training

I can say with certainty that I have developed my analytical skills during my time with Young Mavericks; I now have better insight into defining value and letting the rest go. I am not afraid of making mistakes, in fact, it is better to make mistakes, and as soon as possible, because I then learn from those mistakes sooner. It was an exploration of trial and error, by trying as much as possible I learned a lot more than I would have otherwise and could take big steps quickly.

What does it take to be a successful data scientist?

The first step to becoming a successful data scientist is to have an affinity for data and numbers, if not, it might not be your gig. You have to like trying new things, getting into an adventure every time, with an attitude of “I’ve never done anything like this before, let me give it a try”. You have to feel an unceasing gluttony for new things and energized from embracing the most recent developments.

After Young Mavericks

As Young Mavericks keeps re-inventing themselves, the training sessions get better with every class. This is essential for an organization to keep up with the times, especially in the field of data science.

Young Mavericks Encourages Employees to Travel Sustainably

Stimulate Sustainable Travel

Young Mavericks is joining the youth-driven movement to take ownership of the climate crisis by inspiring their employees to reduce their carbon footprint. Starting in 2020, Young Mavericks is adding a new employment benefit to stimulate more sustainable travel by discouraging the least sustainable means of travel: flying. From then on, anyone who does not use an aircraft within a calendar year will receive two extra vacation days. This policy rewards the employee for reducing their carbon footprint while also giving them the time and freedom to make a difference. 

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Data Science and Data Engineering: Training in Multidisciplinary Teams

This fall, Young Mavericks growth is accelerating, with the hiring of a dozen new trainees – in one fell swoop. Half of them will soon start with our fourth Data Science program; the other half will participate in our first Data Engineering program. They will not only learn the tricks of their trade, but also how to collaborate on scalable insights and models throughout their traineeship. Moreover, they will develop the ability to come up with strong and creative solutions by viewing projects from a multidisciplinary perspective.

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