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Olathe, KS

Internship

Onsite

Intern

Garmin is seeking a full-time Data Scientist Intern to learn and contribute to developing complex datasets, machine learning models, and AI products. The intern will analyze data, support predictive modeling and model pipelines, collaborate with cross-functional teams, and present actionable insights to stakeholders.

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Responsibilities

Contribute to the collecting, cleaning, and preprocessing of large datasets from multiple sources
Contribute to exploratory data analysis (EDA) to identify trends, patterns, and anomalies
Learn to develop and implement predictive models using machine learning and statistical methods
Collaborate with cross-functional teams to translate data insights into actionable recommendations
Learn to build and deploy annotation, training, and evaluation pipelines and automate workflows to improve efficiency
Learn to develop processes and tools to monitor and analyze model performance and data accuracy
Learn to visualize and present data for stakeholders using basic graphics/technologies
Use predictive modeling to enhance user experiences, revenue generation, and business initiatives
Learn and adapt methods from senior team members
Participate in peer reviews and provide constructive feedback
Demonstrate a drive to learn and master new technologies and techniques

Qualification

Required

Pursuing a degree in Computer Science, Electrical Engineering, Computer Engineering, Software Engineering, Aerospace Engineering, Math or relevant field
Excellent academics (cumulative GPA greater than or equal to 3.0 as a general rule)
Familiarity using systems such as SQL, Python or R
Understanding of basic descriptive and inferential statistics
Knowledge in data analysis methods and tools
Demonstrated strong and effective verbal, written, and interpersonal communication skills
Must be team-oriented, possess a positive attitude and work well with others
Driven problem solver with proven success in solving difficult problems
Consistently demonstrates quality and effectiveness in work documentation and organization