Fast Facts
- Wo: Salzburg
- Welche Möglichkeiten gibt es:
- Reguläre Lehre: Die reguläre Lehrzeit ist 4 Jahre
- Lehre mit Matura: Am Freitag werden die Lehrlinge freigestellt und besuchen den 6-stündigen Maturakurs für das jeweilige Fach.
- Verkürzte Lehre: Je nach vorheriger Ausbildung kann die Lehre auch verkürzt absolviert
- Duale Akademie
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ALL ABOUT: CREATING SAFETY BY TECHNOLOGY
- WE ARE PLEASED THAT YOU WOULD BE INTERESTED IN AN APPRENTICESHIP AT EUROFUNK.
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ALL ABOUT: CREATING SAFETY BY TECHNOLOGY
- 1. LEHRJAHR – LOS GEHT‘S!
Du lernst die Grundlagen der Softwareentwicklung und aktuelle Programmiersprachen (u.a. C#, C++, Java) kennen. - 2. LEHRJAHR – BLEIB DRAN!
Du lernst aktuelle Web-Technologien anzuwenden und setzt komplexe Algorithmen um. - 3. LEHRJAHR – FAST GESCHAFFT!
Du bist Teil eines unserer Feature-Teams, entwickelst und testest einfache Features und
lernst die Grundlagen des Projektmanagements kennen. - 4. LEHRJAHR – WIR SIND STOLZ AUF DICH!
Gemeinsam mit deinem Team entwickelst du unsere Software weiter und bereitest dich mit deinen Hauptausbildner*innen auf deine Lehrabschlussprüfung vor.
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RESPONSIBILITIES
- Experience in FMCG, Business, or IT, with strong project management and problem-solving skills
- University Degree in Economics, Business Administration or similar or equal practical experience
- Excellent English skills, German is an advantage
- Analytical mindset with great attention to detail, structured thinking, and a process-driven approach
- Proficient in Microsoft Office; experience with BI tools or coding languages (e.g. Power BI, Tableau, Python, SQL) is a plus
- Strong communication, presentation, and organizational skills to clearly convey insights and solutions
- Self-motivated learner who works well independently and in teams
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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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