5 Model Jobs in Oberösterreich
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RESPONSIBILITIES
- Deep knowledge of material master data and how it drives operations.
- Hands-on experience with SAP MDG-M (SAP MM module experience is a plus).
- Sharp organizational skills and relentless attention to detail.
- Strong problem-solving instincts for ticketing and data/process inconsistencies.
- A process-improvement mindset with a track record of implementing enhancements.
- Clear, effective communication — able to translate complex topics into simple, actionable steps.
- Analytical focus: isolate the core issue, design the fix, measure the impact.
- Proven ability to maintain data accuracy and alignment across systems and stakeholders.
- Ability to thrive in a fast-paced environment with shifting priorities.
- Project management skills are a plus.
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RESPONSIBILITIES
- University degree in a relevant field
- At least 7 years of professional experience in the analytics field, preferably within an FMCG (fast-moving consumer goods) environment
- Knowledge of SAP BW/BI/BW4HANA and SAP SAC is essential; familiarity with other databases (e.g., SAP BDC, Snowflake, Data Bricks) or front-end technologies (e.g., PowerBI, Tableau) is a plus
- Interest in Supply Chain processes and data sets in the context of reporting, analytics, and planning
- Experience in managing projects, delivering and rolling out applications, as well as in running applications and managing their lifecycle for changes and enhancements
- Strong analytical and conceptual skills, paired with a collaborative and proactive mindset, agility, and adaptability to changing circumstances
- Self-motivated team player with good communication skills in English (German is a plus), performance-driven, and result-oriented
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RESPONSIBILITIES
- 3+ years of experience in Data Science. Previous experience working as a Machine Learning Expert is a plus
- Masters or Doctorate in relevant field, for instance: Mathematics, Statistics, Science (including data, behavioural, social, econ, ...)
- Good command of English, both spoken and written. German a plus
- 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
- Support the formulation of technology strategy in response to spotted disruptive external or internal forces and its operationalization.
- Drive IT Landscape Engineering through proactive and deliberate management of the IT landscape beyond investment planning horizons. This involves operationalizing strategy, identifying drivers for change, and defining architecture directions to address these with stakeholders.
- Analyze business strategy and business future-state capabilities to identify Strategic Themes to detect gaps and opportunities for improvement in the current IT Landscape in line with the IT Strategy to enable the business achieving targeted outcomes.
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