Graduate Business Intelligence Intern

Job Description

Graduate Business Intelligence Intern | Port of Seattle

The Tone:
This is a full-time summer internship opportunity at Port of Seattle, located in a hybrid remote/in-office setting in Seattle, WA. The Port of Seattle plays a vital role in moving people and cargo, managing facilities from parks to large airports and container terminals, and promoting economic opportunities. This role contributes to making data tell a clear story, enabling a decision-making culture informed by insights to drive action across the Port’s Aviation, Maritime, and Support Service divisions.

The TL;DR
• Role: Internship
• Type: Full-time, Limited Duration (5 months)
• Location: Hybrid, Seattle, WA
• Pay: $30.30–$32.30 hourly
• Team: Business Intelligence Department
• Mission: This person will assist the Business Intelligence Research Team with data analysis to inform decision-making across the Port’s diverse operations.
• Tech Stack: R, Python, SAS

What You’ll Actually Do
• Analyze complex internal and external data utilizing advanced statistical methods like SEM, HLM, Cluster analysis, and Factor analysis.
• Present clear findings and actionable recommendations to organizational decision-makers using data visualization and storytelling best practices.
• Drive relevant analytical projects to solve real-world business challenges, particularly concerning passenger/travel behavior and other airport-related data.
• Continuously enhance technical skills, analytical thinking, communication, performance measurement, and continuous improvement practices.

The Must-Haves
• Background: Currently enrolled in a Master’s program or a recent graduate (within 1 year) in a degree program such as business analytics, data science, statistics, information management, or a related discipline.
• Experience: Demonstrated experience in data manipulation and knowledge of advanced analytical methods and practices.
• Skills: Proficiency in advanced statistical methods (e.g., SEM, HLM, Cluster analysis, Factor analysis), understanding of data visualization and information design concepts, strong written and verbal communication skills, and experience with SAS, R, Python, or other statistical software.