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Data Scientist Fraud & Risk Leverage data science to block malicious behavior

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How do you make our customers happy?

Together with our 47,000 partner sellers, is changing retail to make daily life easier for 13 million customers. By now, those customers swipe and click through a catalog of over 33 million articles. Given those huge numbers and our rapid growth, our retail tech platform is prone to misuse. So we are constantly stepping up our efforts to deter abuse, e.g., by leveraging data science to detect and mitigate malicious behavior. We want your help to build innovative solutions that future-proof fraud detection, reduce the risks of malicious behavior, and – last but not least – stop miscreants dead in their tracks.

Your responsibilities as Data Scientist Fraud & Risk

  • Help build and continually optimize data science solutions that identify and mitigate platform risk exposure
  • Determine indicators (patterns) of potential fraud and conceptualize ways to automatically detect instances
  • Engage with our ‘hardcore’ tech and business communities to demonstrate the added value of your models, cultivate commitment
  • Claim end-to-end ownership of your models and solutions: from ideation to implementation

In this role, you will co-create and validate predictive and risk models that automate and/or enhance our fraud detection capabilities. In short: you aim to spot and stop potential platform misuse in real time! Together with colleagues from a variety of professional backgrounds and with diverging skill sets, you identify fraud patterns (what are the subtle and not so subtle indicators?) and devise ways to detect and stop misuse early and effectively. That entails conceptualizing innovative solutions (we do not have many platform peers, so copy/pasting solutions is rarely an option) and leveraging data from a wide range of sources.

The role calls for a Data Scientist who doesn’t subscribe to the ‘science for science’s sake’ mindset, because understanding the purpose and ambitions of the surrounding business is key to maximizing your impact. The same goes for an eagerness to enable engineers and convince less tech-savvy colleagues of the added value of your predictive models. So, data science credentials aside, the team is looking for someone who speaks up easily, enthusiastically sells their ideas, and can level with any and all stakeholders, regardless of their field of expertise and data science prowess.


Why you can make a difference

To be successful as Data Scientist Fraud & Risk, you obviously need the right credentials: a background in data science (AI or equivalent) and at least 3 years of relevant work experience. This ideally comprises a mix of Machine Learning / Deep Learning / Link Analysis / Risk Modeling techniques. We also expect a proven ability to program in Python, write queries in SQL and use libraries like sklearn, keras, and/or tensorflow. Bonus points for experience with Neo4j, the Google AI platform, and Java.

Technical skills aside, we’re looking for a team member who is eager to work on data science projects from ideation to production phase. On a more personal level, we value a strong drive to help people from divergent backgrounds and skill sets to understand your models, as well as strong social skills. Moreover, the team loves to share, both ‘internally’ and with the broader Data Science community. Our team also has a soft spot for the ‘just do it’ mindset. If you share that mentality, awesome!

3 reasons why this is(n’t) for you

  • Yes, if you are keen to collaborate with the engineers on your team: they build what you envision, so the closer the bonds, the better
  • Yes, if mixing and mingling with the Fraud & Risk crowd (and beyond) is your thing: you are eager to spread the Data Science word
  • Yes, if you feel responsible for turning ideas into realities
  • No, if your attention span plummets after the POC phase
  • No, if neural nets are your answer to anything and everything
  • No, if you like flying solo #allthatairspaceismiiiiiiiiiiine!

Where you’ll work

At the premier online retail tech platform in the Netherlands and Belgium. A platform where 13 million Dutch and Belgian customers can choose from over 33 million articles. A platform that helps roughly 47,000 commercial partners run their business. And a platform that will never be ‘finished’, because has been reinventing retail since 1999 and we always will be. If there’s a better way to do something, we’re working on it! Together with our customers, partners, and about 2,400 colleagues. And hopefully together with you! The setting is open, pioneering, and autonomy is actively encouraged. In this role, you work closely with our Product Owner, Business Analyst, fellow Data Scientists, and Software Engineers., de winkel van ons allemaal (the store of us all). This is the story we work on every day. It is our belief, that this will grow even stronger when many different people add their uniqueness to our story. We invite you to share your story with us. Because when you bring different people together, the most beautiful things will arise.

What you get

What you get

  • A blue and safe landing

    We warmly welcome our new colleagues, so they feel home as soon as possible. During your onboarding program, we give you all the ins and outs about!
  • Money and more...

    Working at is challenging and therefore you get something in return. Besides salary, you will receive a yearly bonus, holiday allowance, holiday entitlement of 29 days, travel allowance, group insurance and more.

How it works

  1. Carefully, we take a look at your application. Within 2 weeks you know if we invite you for an interview.
  2. We call you to set up an interview. And since we’re already talking: feel free to ask any question you may have.
  3. In this first interview we’ll get to know each other. We want to find out more about you. Work experience is interesting, but we also want to find out more about you as a person. Together, we’ll find out if this job is a match made in heaven.
  4. Before the next interview we will ask you to take an online assessment. We’ll also discuss the position and your team in depth.
  5. 2 interviews are usually enough to see if it’s a match. And if you agree… well, it’s the beautiful beginning of your career at :)

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