RESPONSIBILITIES
- 5+ years of experience in Data Science. Previous experience working on Data Science topics in Operations / Supply Chain is a plus.
- Programming: proficient in at least one of R, Python, SQL with the ability and willingness to learn the other two.
- Data Literacy: ability to prepare datasets ensuring top quality such that essence of said data and the implications for the problem at hand can be grasped quickly.
- Technical Literacy: applied understanding of modern computing allows the candidate to do things which go beyond the strict definition of Data Science (git, API calls, web crawling, …).
- Statistical Reasoning: applied understanding of Stats and Probability and know how to use these tools to reduce uncertainty in a business context (regression, visualisation).
- Project Management: able to navigate evolving requirements, prioritise effectively, and scope work in a way that balances impact, effort, and stakeholder needs.
- Presentation Skills: present coherent data stories at the appropriate level of abstraction given the audience.
- Stakeholder Management: skilled at building mutually beneficial connections with functional stakeholders.
- Pragmatic Critical Thinking: intuitively consider relevant costs/benefits in all decisions and act accordingly.
- Outcome Driven: highly motivated to add value and to demonstrate that impact to the organisation.
- Scientific Reasoning/ Scoping: ability to define and formulate new questions, in addition to answering given ones.
- Grit: proven capability to see things through to the end even if initial feedback is discouraging.
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RESPONSIBILITIES
- 4+ years of experience in Data Science. Previous experience working on Data Science topics in Operations / Supply Chain is a plus.
- Masters or Doctorate in relevant field, for instance: Mathematics, Operations Research, Science (including data, computer, behavioural, social, e-con, ...).
- Programming: know at least one of R, Python, SQL with the ability and willingness to learn the other two
- Data Literacy: ability to prepare datasets ensuring top quality such that essence of said data and the implications for the problem at hand can be grasped quickly
- Statistical Reasoning: theoretical and applied understanding of Stats, Probability and ML Algorithms and know how to use these tools to reduce uncertainty in a business context (regression, visualization)
- Technical Literacy: applied understanding of modern computing allows the candidate to do things which go beyond the strict definition of Data Science (git, API calls, web crawling, …)
- Presentation Skills: present coherent data stories at the appropriate level of abstraction given the audience
- Stakeholder Management: skilled at building mutually beneficial connections with functional stakeholders
- Pragmatic Critical Thinking: intuitively consider relevant costs/benefits in all decisions and act accordingly
- Outcome Driven: highly motivated to add value and to demonstrate that impact to the organization
- Scientific Reasoning/ Scoping: ability to define and formulate new questions, in addition to answering given ones
- Grit: proven capability to see things through to the end even if initial feedback is discouraging
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RESPONSIBILITIES
- 7+ years in IT infrastructure architecture or related roles.
- Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.
- English mandatory, German optional.
- Proven expertise in data integration platforms (e.g., Azure Data Factory) and/or disaster recovery planning.
- Strong knowledge of hybrid cloud environments (Azure, AWS).
- Proficiency in virtualization, storage, networking, and backup technologies.
- Familiarity with automation tools and Infrastructure as Code (IaC).
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