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Internship in Critical Infrastructure and Machinery (d/f/m) Start December 2026

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Austria📅 23/10/2026

Descripción

1 Internship in Critical Infrastructure and Machinery (d/f/m) Start December 2026 Adhesive Technologies / Quality Engineering / Austria, Vienna / Full Time 38,5 / LimitedAbout this PositionJoin our Commercial Excellence team and gain deep insights into project management and business analytics in an international environment. As part of the Project Management Office, you will support key projects, drive process improvements, and help transform data into actionable recommendations for decision-makers. What you?ll do * Active part in a global team within Adhesive Technologies, supporting commercial decision-making for Infrastructure Protection and Repair through data and analytics * Development, maintenance and continuous improvement of dashboards and analytical tools in Excel and Power BI for global sales pipelines, partnerships, customers and projects * Translation of business requirements into KPIs, data analyses and visualizations to support strategic decision-making * Close collaboration with international commercial teams and senior management to define reporting requirements, validate data and optimize analytical solutions * Analysis, validation and consolidation of CRM, sales, customer, project and partnership data to ensure high data quality and consistency * Preparation of actionable insights and recommendations for international stakeholders, including documentation of KPIs, reporting processes and data standardsWhat makes you a good fit * Full-time internship for a period of 6 months, Starting in December 2026 * Active student of Business Administratio, Engineering, Business Analytics or related studies * Relevant practical experience, preferably in consulting, strategy or business development * Excellent English language skills and advanced communication skills required * Strong analytical skills with proficiency in Excel (pivot tables, formulas, data modeling) and Power BI * Ability to manage and clean large datasets with attention to detail and data int
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