How do you make our customers happy?
Do you have a passion for data? Can you explain complicated models in a simple way? Then Data Science at bol.com is the right place for you! Within a multidisciplinary team (with data scientists, engineers, business analyst and a product owner), you will tackle one of our many challenges. As part of this team, you get the chance to join their day-to-day processes. Besides your own project and thesis there is also room to work on tasks within this team which directly improve bol.com for our customers. You will work together with professionals who love to share their knowledge, allowing you to learn the ins and outs of the fast-growing market we’re in. And if your work is a success, it will be deployed, which means that your innovation will become part of our platform. In the meantime, there will be plenty of opportunities to get to know your colleagues: with (digital) drinks, gaming sessions, hackathons and monthly knowledge exchanges. No better way to kickstart your career.
What you will do
As a Data Science intern, you will work on one of the many complex challenges within bol.com. By crunching our many terabytes of data, you will investigate how this information can be used to improve our processes. Being technically well-versed is an absolute must to succeed. Together with your supervisor you will find a model-based solution to a real problem within e-commerce and a fast way to test its feasibility. We pay a lot of attention to the effective translation of results into concrete actions, implementations and/or recommendations during your internship. This will allow you to cover the complete process from challenge to solution.
We have positions in the domains of Fraud & Risk, Platform Quality and Recommendations.
You have the chance to work on one of the following topics:
- Fraud & Risk: improving our current fraud and risk processes with machine learning or risk modelling. You either: Build a complementary machine learning model to our rule-based decision-making engines; perform anomaly detection on fraudulent customer behavior; or any great idea from your side.
- Platform Quality: detecting intent and/or emotion in a large corpus of possibly controversial product texts (e.g. consider topics such as hate speech or conspiracy detection).
- Recommendations: customer interest modeling based on interactions data. Using short- and long-term customer interest representation learning to make relevant and diverse product recommendations.
What you bring along
- Preferably you study Data Science, AI, Computer Science, Econometrics, or are enrolled in a comparable master degree program
- Knowledge of machine learning techniques, depending on the team: for Fraud & Risk: an emphasis on risk modelling, imbalanced data and/or anomaly detection; for Platform Quality: an emphasis on Natural Language Processing; and for Recommendations: an emphasis in deep learning, specifically generative models.
- Experience with programming in Python
- Available for 4 or 5 days a week, for at least 3 months
Note: For all of our internships, you have to be enrolled at an educational institution for the complete duration of the internship at bol.com. You are able to register for a regular internship, or a graduation internship.
Please send in your CV and a motivation containing information about your educational background, start and duration of your (thesis) internship and for how many days a week you will be available.
Wij creëren een omgeving waarin we de kracht van diversiteit benutten.
De voordelen van een blauw hart
De cultuur en het kantoorOnze collega’s werken keihard om het dagelijks leven van onze klanten makkelijker en leuker te maken. Maar dit doen we uiteraard wel in een inspirerende en creatieve omgeving met leuke activiteiten!
Flexibele werkcultuurWe voegen het beste van twee werelden samen, zodat de balans tussen organisatie- en individuele behoeften goed blijft. Dit betekent 50% werken op kantoor en 50% vanuit huis.
De extra'sDenk hierbij aan trainingen, een lekkere lunch, een telefoon en eventueel een leaseauto, wanneer dit nodig is voor het uitoefenen van je functie.