In sintesi
- Mansioni: Analizza dati per migliorare le performance della catena di approvvigionamento e supporta decisioni strategiche.
- Azienda: Azienda innovativa nel settore della supply chain con un ambiente collaborativo.
- Benefit: Stipendio competitivo, orari flessibili e opportunità di lavoro remoto.
- Altre informazioni: Ambiente dinamico con ottime opportunità di crescita professionale.
- Perché questo lavoro: Trasforma i dati in intuizioni e fai la differenza nel mondo della supply chain.
- Qualifiche: Laurea in Data Analytics o campi correlati; esperienza in analisi dei dati richiesta.
La retribuzione prevista è compresa tra 30000 - 50000 € per anno.
The Data Analytics Specialist supports the Regional Supply Chain organization by delivering accurate, insightful, and actionable analytics that drive operational performance and business decision-making.
The role acts as a key business partner across Planning, Procurement, Operations, Logistics, and Customer Service, ensuring visibility of performance, consistency of KPIs, and data-driven decision making throughout the Supply Chain network.
This position is responsible for transforming data into business insights, identifying trends and performance gaps, supporting SIOP processes, and driving continuous improvement initiatives across the region.
Key Responsibilities
- Develop and maintain Supply Chain performance dashboards and KPIs, ensuring data accuracy, consistency, and visibility across the organization.
- Provide analytical insights and reporting to support strategic and operational decision-making for Supply Chain leadership.
- Support SIOP processes through demand, inventory, capacity, and forecasting analysis, identifying risks and improvement opportunities.
- Partner with Operations, Procurement, Logistics, Customer Service, and Planning teams to monitor performance and drive business results.
- Develop automated reporting solutions and analytical tools to enhance efficiency, data quality, and decision-making capabilities.
- Support continuous improvement initiatives through performance measurement, root-cause analysis, and benefits tracking.
Qualifications & Experience
Education
- Bachelor’s Degree in Data Analytics, Statistics, Supply Chain Management, Industrial Engineering, Business Analytics, or a related field.
- Master’s Degree and/or professional certifications (APICS, Lean Six Sigma, Power BI, Tableau, SQL) are considered a strong advantage.
Experience
- 3-5 years of experience in Data Analytics, Business Intelligence, Supply Chain Analytics, or a related analytical role.
- Previous experience supporting Supply Chain functions such as SIOP, Operations, Procurement, Logistics, or Customer Service.
- Experience in manufacturing, industrial, or operations-driven environments is highly preferred.
SKILLS
Strong proficiency in
- Power BI, Tableau, or similar BI tools
- Excel (advanced), Power Query, and data modeling
- SQL and/or database querying
- ERP systems (SAP/Oracle)
- Strong understanding of supply chain KPIs, processes, and data structures.
- Ability to transform complex datasets into clear, actionable insights.
What we offer
- Competitive salary package range from €30,000 to €50,000, based on experience and qualifications.
- Flexible working hours and remote working opportunities to support a healthy work-life balance.
- Global Headquarters
Dayco Incorporated
401 S. Old Woodward Avenue, Suite 308
Birmingham, MI 48009
United States
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Data Analytics Specialist datore di lavoro: Dayco Canada Corp
Dayco Incorporated è un datore di lavoro eccezionale, offrendo un ambiente di lavoro collaborativo e innovativo nel cuore di Birmingham, MI. Con opportunità di crescita professionale e un pacchetto retributivo competitivo, i dipendenti possono godere di orari flessibili e opzioni di lavoro remoto, promuovendo un equilibrio tra vita lavorativa e personale. La cultura aziendale si concentra sulla valorizzazione delle competenze analitiche e sull'impegno per il miglioramento continuo, rendendo ogni giorno significativo e gratificante per i membri del team.
