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Data Scientist Recommendations You Build it, You Run It, You Love it

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How do you make our customers happy?

Recommendations are at the heart of shopping at Even veteran shoppers can use a little help when there are 41 stores and over 20 million items to choose from. That’s why we deploy a recommender system that helps customers discover and choose the perfect products for them. From suggesting products based on viewing and buying signals to providing deep category entrances and adding a touch of personalization, recommender systems can transform the customer journey from an uncomfortable paradox of choice to a smooth and enjoyable activity. We see this as an integral part of the customer experience. And we’re fortunate that our customers provide us with all the input we need to continue improving our recommendations on a daily basis. Can you further improve and run’s recommender systems for millions of items and users?

Your responsibilities to provide the best recommendations to our customers

As a Senior Data Scientist in the recommendations team, you improve the recommender systems that drives our customer experience and coach and mentor team colleagues. Together with the data scientists, data engineers and software engineers on your team, you apply your ML and statistical expertise and experience to develop and experiment with applied ML systems that drive conversion and sales, using metrics such as CTRs and order rates. You accomplish this with state-of-art learning technologies (such as neural nets) as well as old-fashioned bandits and linear learners. Whatever gets the job done because, you guessed it: we take a pragmatic approach. Pragmatism is also necessary in your communication style. You’ll sharing your ideas with a broad audience, from store specialists to C-level executives, across a large part of our organization (as this is an important business domain, albeit a highly technical one). And of course, we do not conduct data science as an intellectual exercise but in order to add value in a production environment. Given our scale and performance requirements, this also calls for engineering skills. in numbers doesn’t drop numbers to impress, but we do want to put the responsibilities of this position in perspective. We’re talking about

  • Sorting through over 20 million products
  • For over 9.5 million customers, who
  • Can place 17 orders per second, sustained (Black Friday, 2017)


3 reasons why this is(n’t) for you

  • Because you want to apply your technical background and applied ML expertise (preferably in recommender systems!) at scale
  • Because you thrive in an inclusive and cooperative cross-functional environment
  • Because you think in code and engineering
  • Because you’re a 100% academic researcher who considers practical applications inconsequential
  • Because you have no affinity with software engineering and shrug when we mention stuff like NoSQL, cloud, and massive parallelization
  • Because you only want to work on new things and hate to take care of legacy when needed.

Where you’ll work

As Senior Data Scientist you’ll be at the center of our data-intensive landscape. Our business model is focused on technology, and data-driven improvements that drive innovation for our customers are our bread and butter. Retail & Data is a unique team of data professionals within this landscape, both in terms of its size and expertise – features that make for a compelling work environment. And because the cross-functional teams also include representation from the business units, you’ll quickly gain a complete picture of the (needs of the) organization. The setting is informal, pragmatic and innovative. Our success is based on collaborating as equals and continuously learning from each other. So it’s only natural that you are also the ambassador for your discipline within And that you can present complex ideas to non-expert audiences with a focus on customer value. You can achieve good things alone, but even better things together. We have a strong devops credo: You Build it, You Run It, You Love it. This is even more important when you consider that we are one of the few data science teams with years of experience and successful legacy.

What you get

What you get

  • Attention to you

    We are continuously focused on innovation and getting better every day. Because we work in a dynamic environment and our organization is growing rapidly, your development will grow together with
  • 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.
  • Besides work

    At there is also a lot to do after work. Most of the activities are initiated by our own colleagues. That’s why all activities are very diverse and always voluntary. For example playing sports, team activities, Friday drinks or meetups.

How it works

  1. Your application
    Carefully, we take a look at your application. Within 2 weeks you know if we invite you for an interview.
  2. First contact
    We call you to set up an interview. And since we’re already talking: feel free to ask any question you may have.
  3. First date
    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. Your next interview
    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. Is this love?
    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 :)

Any questions? Contact

Apply right away You Build it, You Run It, You Love it

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