Job: Data Scientist
We are looking for data scientists that feel at home at the intersection between science, mathematics, machine learning, business and computer science. You may come from a science background or have experience in a environment driven by scientific methodology. You also know their math and statistics and know how to apply this to actual problems.
You have dabbled with machine learning, NLP, or optimization modeling. You know how to create visualisations in order to tell a story (and why you should avoid pie charts!). And very importantly, since we believe in developing actual products for our customers instead of just providing them with algorithms or models, our data scientists also enjoy writing programs that run on servers and talk to databases.
As a data scientist you are capable of rapidly learning about the domain of our customers, while taking up the challenge of making sense of their operational and otherwise collected data. You communicate well and are capable of explaining what you do to customers in understandable terms. You are the kind of person that can explain in layman terms why we call a naïve Bayes classifier naïve.
When it comes to data analysis you do not expect data to be clean, concise, well organized, well documented, consistent or complete. You make do with what you get and don't make assumptions. You understand the strengths and weaknesses of different models and can effectively reason about when to apply various combinations. You're not a one trick pony.
The Data Scientist role is a senior postion with a pivot role in our clients teams, therefore at least 2 years of relevant professional experience is required. We like to be amazed, though, so if you have done something outstanding during your studies, like contributing to open source projects or starting your own company, we encourage you to apply.
Also, since most of our customers operate in the Netherlands, a working knowledge of Dutch is a requirement. Read more about working as a Data Scientist:
Meet Your New Colleagues
We sat down with a few of our data scientists to talk about their work. Topics discussed are for example work-life balance, writing intellectually challenging code, and giving back to the community.
DRIVEN is a series of video portraits of data scientists and data engineers, who talk openly about their work and personal life and finding a proper balance between the two. The series consists of interviews with one guest per episode both inside and outside a studio setting.
In this episode of DRIVEN, Giovanni talks about elegance, open source, his family life, the trait of curiosity, his contribution to the team, and the reason for storing 15 liters of wine in his basement.
Physicist Rodrigo wakes up early, energized by the promise of a new day of complicated things to solve. One thing in his life is not so complicated, though. And that's his morning ritual of peanut butter banana sandwiches.
Growing up in Siberia, Nelli felt a strong desire to broaden her horizons. It was only a matter of time before she moved away and began exploring. Just like wild animals and sheer heights don't intimidate her much, she's not afraid to dive deep into untrodden datasets.
Lukas is a true scientist who likes to discover new things; whether it's in human psychology, in corporate data or in the breeding habits of owls. Being outdoors has always been a big part of his life. For Lukas, nature is the place where he goes to relax and explore.
Laidback Jelte generally takes things as they come. He gets excited by the energy of early-stage projects and initiatives. Whether it's developing data-driven apps, training other data scientists, or engaging in sports; when Jelte get's started it's hard to stop him.
Prefered general knowledge includes:
- Machine Learning
- Optimization modelling
- Data Visualisation
- Data structures
Preferred skills / tool experience includes:
- Analysis tools: Python + Pandas / R / Julia / Matlab
- Using relational databases
- Working with Linux, including writing Bash scripts
- bonus: Software engineering practices
- bonus: Hadoop / Hive / Spark / MapReduce
- bonus: NoSQL databases
As a Data Scientist, you understand the strengths and weaknesses of different models and can effectively reason about when to apply various combinations. You're not a one trick pony.