Graduation: Supply chain risk assessment through an analytical digital twin
Core
Develop a data-driven analytical digital twin to assess supply chain delivery risks and optimize logistics networks.
Role type
Master's level data science student (supply chain analytics)
Builds
Predictive risk models and network optimization approaches for logistics
Domain
Supply chain management and logistics
Deliverable
production ML models
Required skills
Python, SQL, data analysis, problem-solving, programming
Preferred skills
Operations research, optimization, digital twins, large datasets
Technologies
Python, SQL
Responsibilities
Map logistics network dependencies, analyze historical operational data, develop digital twin components, evaluate risk assessment applications, document research findings
