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Software Engineer Machine Learning The brain that makes hearts beat faster

Bachelor / Master
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How do you make our customers happy?

With over 8 million customer interactions per year, Customer Service is a complex and data intensive business domain. And wouldn’t be if we didn’t leverage that enormous wealth of data to lift our customer service to a higher level. For example, by identifying trends early and using these insights to improve the service experience. Data as a vector to our customer’s hearts! Do you have the brains to fulfill this ambition?

Your responsibilities as a Software Engineer Machine Learning

You use your in-depth knowledge of Machine Learning and Business Intelligence to better anticipate customer needs and perfect the service experience. This starts with designing systems to process large data sets intelligently and scalably. You will focus on structured and unstructured data that you’ll process with SQL and/or data processing frameworks. Your strong quantitative background will prove an invaluable asset. We also challenge you and our Customer Service stakeholders to think about the kind of data we need to optimize the customer experience and determine (and calculate) relevant KPIs and other metrics. This will enable us to distill trends and our customers’ needs and expectations from our data at an increasingly early stage. And you will help your colleagues use these intelligent services, and share your insights and challenges with our engineers and data scientists.

What we need you for

Because the complexity of the challenges is huge, so they can only be overcome by a quantitative Software Engineer with experience in designing and implementing models and algorithms. For example pertaining to classification and regression problems. You know how to visualize data and have expert knowledge of algorithms and methods to train and evaluate models. Moreover, you can apply this knowledge to specific problems, for example to ‘humanize’ chatbot Billie and to predict customer questions.

3 reasons why this is(n’t) for you

  • Because you proudly carry a Master’s degree in Computer Science, Mathematics, AI or similar
  • Because you know SQL, Java and Python inside-out, and have demonstrable Machine Learning skills
  • Because you either are experienced in Natural Language Processing, MapReduce frameworks (e.g. Apache Beam or Apache Spark) or want to master these soon
  • Because you are more of a scientist than a developer; practical use is just a byproduct
  • Because you tend to shy away from contact with business stakeholders
  • Because you don’t subscribe to the idea that data is THE vector to customer hearts

Your team

Where you’ll work

Take a look around!

As Software Engineer Machine Learning you will develop tools that grant us the insights we need to take action. Action to improve the customer experience for millions of customers. Our business model is focused on technology and data-driven improvements, as we consider data the fuel for customer-driven innovation. This makes an inspiring work-environment. Not just in its depth, but also in its breadth, as we work in cross-functional teams in which the business is strongly represented. Success in data science takes more than you’ll learn at university and is the perfect place to further your education. The setting is informal, unpretentious and innovative. Our strength is a sense of cooperation among equals that drives us to continuously improve ourselves and each other. You can achieve good things alone, and greater things together.

What you get

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 Are you the brain that makes hearts beat faster?

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