[Data Analysis & Insights Generation]
- Analyze large, complex datasets to identify trends, patterns, and derive key underlying drivers of performance and how to further optimize them
- Identify opportunities for automation, process optimization, and innovation using data-driven approaches
[Data Science Solutions]
- Design, build, and deploy machine learning models and algorithms to solve business challenges and improve operational efficiency
- Collaborate with other team members to integrate AI/ML solutions into use case applications
- Train engineers and technicians to leverage the insights for improving their day-to-day performance
[Data Visualization & Reporting]
- Create interactive dashboards, reports, and visualizations to communicate insights to non-technical stakeholders.
- Use tools like Power BI, or Python libraries to present findings effectively
[Collaboration & Stakeholder Engagement]
- Participate as a data scientist in multi-disciplinary project teams aiming to improve the performance of our production environment in specific areas such as logistics and supply chain, assembly, maintenance, and quality
- Act as a subject matter expert on data science, providing guidance and support to project teams
- Recommend and implement new tools, techniques, and methodologies to enhance project outcomes