Job description

Data Collection, Cleaning & Structuring
• Retrieve data from multiple internal sources (WMS, ERP, Excel files, internal databases).
• Clean and normalize datasets: remove duplicates, handle missing values, and ensure consistency in formats and definitions.
• Document data flows and metadata to ensure traceability and standardization across countries.
Exploratory Analysis & Modeling
• Analyze operational data to identify trends, anomalies, and bottlenecks in logistics flows (storage, picking, dispatch, returns).
• Develop dashboards and visualizations showing key performance indicators: productivity, error rates, lead times, cost per unit, service levels.
• Apply statistical or mathematical methods (simple regressions, clustering, time series, functions) to better understand operational phenomena.

Process Automation
• Write scripts or small applications/macros to automate repetitive manual tasks (data cleaning, report generation, automatic email updates, etc.).
• Use tools such as Python, VBA, or equivalent, and develop light front-end interfaces using HTML or Java when needed.
• Document automation logic and maintain scripts for long-term use.
Internal Tools & Application Development
• Create or contribute to internal applications using Power Apps, Power Automate, or other low-code tools to digitalize processes (data collection, workflow tracking, approvals, etc.).
• Ensure proper integration of these tools with existing systems, including potential API connections.
Reporting & Dashboards
• Build and maintain Power BI dashboards for operational, excellence, and management stakeholders.
• Prepare regular and ad hoc reports highlighting analytical results, trends, and recommendations.
• Set up automated data refreshes and alerts for critical KPIs.

Communication & Knowledge Sharing
• Present analytical findings to non-technical stakeholders, clearly explaining the operational implications.
• Document scripts, processes, and dashboards to enable easy understanding and maintenance.
• Share knowledge and contribute to building a data-driven culture within the regional team.
• Include links to any personal or academic projects demonstrating your technical skills (GitHub, Power BI, portfolio, etc.).

Requirements
Someone with:
• Master’s degree in Mathematics, Applied Statistics, Data Science, or related field (mandatory).
• Strong background in mathematical reasoning, modeling, and data analysis.
• Technical proficiency in:
• Python(Pandas), VBA, HTML, Java(Optional)
• Power BI, Power Apps, Power Automate, Power Query
• Advanced Excel (pivot tables, forecasting)
• SQL
•
• Experience through internships, academic projects, or personal initiatives in analytics or process improvement.
• Bilingual in French and English (spoken and written).
• Methodical, detail-oriented, and proactive, with the ability to link numbers to real-world operations.
• Comfortable working in multicultural, fast-paced environments.