VIE: Data Scientist [ ]
Role details
Job location
Tech stack
Job description
Amaris Consulting is looking for a Data Scientist to join a forward-thinking industrial innovation team through the VIE (Volontariat International en Entreprise) program. Based in Eindhoven, Netherlands, this is a unique opportunity to work on real-world machine learning applications that drive measurable business impact - from predictive maintenance of high-tech equipment to optimizing global production processes.
You'll be embedded in an internal consultancy team that partners with business units to solve complex operational challenges using data. This is not a research or academic role - we're looking for someone who has successfully deployed machine learning models into production and understands how to maintain and improve them in real-life settings Need explanatio...AMANL.docx.
The role requires working on-site at least three days per week in Eindhoven Need explanatio...AMANL.docx., Partner with business stakeholders to translate real-world problems into data-driven solutions - from defining requirements to delivering models that create impact Design, develop, and deploy machine learning models into production environments Own the end-to-end ML lifecycle, including feature engineering, model validation, deployment, monitoring, and performance improvement Work with unstructured and industrial data from diverse sources (e.g., sensor data from equipment used globally) Build dashboards and analytical views using QlikView and Qlik Sense to communicate insights to non-technical stakeholders Collaborate closely with data engineers, product teams, and business managers to ensure scalable and reliable solutions, Contribute to impactful and innovative engineering projects in the Netherlands. Join an international consulting environment focused on growth, digital transformation, and continuous learning. Collaborate with major global industry leaders across sectors such as technology, manufacturing, and life sciences. Enjoy a hybrid work model with a blend of office and remote work. Work within a diverse, international network supported by global hubs and centers of excellence. Join as a VIE, a unique international experience with professional growth and support, At Amaris, we strive to provide our candidates with the best possible recruitment experience. We like to get to know our candidates, challenge them, and be able to give them proper feedback as quickly as possible. Here's what our recruitment process looks like:
Brief Call: Our process typically begins with a brief virtual/phone conversation to get to know you! The objective? Learn about you, understand your motivations, and make sure we have the right job for you!
Interviews (the average number of interviews is 3 - the number may vary depending on the level of seniority required for the position). During the interviews, you will meet people from our team: your line manager of course, but also other people related to your future role. We will talk in depth about you, your experience, and skills, but also about the position and what will be expected of you. Of course, you will also get to know Amaris: our culture, our roots, our teams, and your career opportunities!
Case study: Depending on the position, we may ask you to take a test. This could be a role play, a technical assessment, a problem-solving scenario, etc.
As you know, every person is different and so is every role in a company. That is why we have to adapt accordingly, and the process may differ slightly at times. However, please know that we always put ourselves in the candidate's shoes to ensure they have the best possible experience. We look forward to meeting you!
Requirements
Do you have experience in QlikView?, Professional experience as a Data Scientist in an industrial, manufacturing, or production environment - not academic or research-only projects. Proven track record of deploying ML models into production and monitoring their real-world performance Strong experience in translating business needs into model requirements through direct stakeholder collaboration
Hands-on skills with: QlikView and Qlik Sense Python (or similar) for data analysis and machine learning Machine learning techniques (e.g., regression, classification, clustering, time series) Fluency in English (written and spoken) - mandatory for cross-functional communication Ability to explain technical trade-offs and model behavior to non-technical audiences Passion for solving real industrial problems - not just building models, but ensuring they work in practice.
