Arcadis
Data Analyst
ArcadisIreland3 days ago
ContractProduction, Information Technology +1

About the Role:

We are seeking a highly motivated and skilled Data Scientist to join our Global Supply Chain team. This role is crucial for optimizing the complex pharmaceutical supply chain, which includes raw material sourcing, manufacturing, logistics, and distribution. The ideal candidate will use advanced analytics, machine learning, and statistical modelling to provide actionable insights that drive efficiency, reduce costs, and improve reliability across our global network.


Key Responsibilities:

  • Forecasting and Predictive Modelling: Develop and implement predictive models for demand forecasting, inventory optimization, and supply risk prediction.
  • Network Optimization: Analyse and model the supply chain network to identify bottlenecks, assess risk, and optimize resource allocation for improved logistics and inventory management.
  • Data Analysis: Perform in-depth analysis of supply chain data to identify trends, inefficiencies, and opportunities for improvement.
  • Performance Monitoring: Build automated dashboards and reports using tools like Power BI to provide real-time insights into key supply chain metrics for stakeholders across the organization.
  • Collaboration: Work closely with logistics, planning, manufacturing, and commercial teams to align analytical models with operational needs and business constraints.
  • Data Management: Clean, process, and harmonize large, dynamic datasets from various supply chain systems to ensure data accuracy and consistency.
  • Problem-Solving: Utilize strong problem-solving abilities to address complex supply chain challenges, translating business questions into analytical projects.
  • Communication: Clearly and effectively present findings to both technical and non-technical audiences, influencing business decisions with data-driven insights.


Education:

  • Qualification in Data Science, Statistics, Computer Science, Engineering, or a similar quantitative field.

Technical Expertise:

  • Strong experience with machine learning algorithms (e.g., classification, regression, time-series analysis) and statistical methodologies. Experience with SQL for data extraction and manipulation. Proficiency with business intelligence and data visualization tools, specifically Power BI, to create interactive reports and dashboards.


Preferred Qualifications:

  • Experience in a regulated industry, with an understanding of compliance requirements.

Key Skills

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