Project Overview
Today, we leverage basic analysis techniques to transform this data into actionable insights for our customers. This project aims to take that to the next level by enhancing data models and creating sophisticated algorithms that will improve machine performance insights across its lifecycle. In this project you will have the opportunity to work on a high-impact initiative that will challenge conventional digital twin concepts and deliver real value to both internal stakeholders and customers.
Key Responsibilities
Data Collection & Analysis: Familiarize yourself with the different data sources that exist today. Conduct exploratory data analysis to identify trends, gaps and opportunities.
Data Modeling: Develop and refine data models to predict key performance indicators over the complete lifecycle of the equipment. This may involve regression models, classification, or other machine learning techniques.
Collaboration: Work with cross-functional teams, including engineering and product management, to validate findings and ensure data models align with existing understanding of the machine lifecycle.
Visualization: Create data visualizations and a strategy to make insights easily accessible for internal and external stakeholders.
Innovation: Explore opportunities to enhance Dynapac's digital ecosystem by proposing innovative features or identifying efficiency gains based on your analysis.