Data Scientist Intern: ML, Data Pipelines & Insights

Garmin; Louisville (CO); On-site; USD 25,000 - 42,000; Full time

Benefits offered by this job

Garmin Intern Benefits

Job summary

Garmin is seeking a full-time Intern - Data Scientist at our Louisville, CO site. You will learn and train to develop large data sets, build ML models, and translate insights into actionable AI products.

Collaborate with cross-functional teams to drive data-driven decisions, design data pipelines, and monitor model performance while gaining hands-on experience in a leading tech company.

Qualifications

• Pursuing a degree in Computer Science, Electrical Engineering, Computer Engineering, Software Engineering, Aerospace Engineering, Math or relevant field.
• GPA 3.0+ preferred.
• Familiarity with SQL, Python or R.
• Understanding of basic descriptive and inferential statistics.
• Knowledge of data analysis methods and tools.
• Strong verbal and written communication; team-oriented.
• Driven problem solver with good documentation.

Responsibilities

• Collect, clean, and preprocess large datasets from multiple sources.
• Perform EDA to identify trends and anomalies.
• Develop and apply predictive models with ML and statistics.
• Collaborate with cross-functional teams to translate insights.
• Build and deploy annotation, training, and evaluation pipelines.
• Monitor model performance and data quality.
• Visualize data for stakeholders using basic graphics.

Skills

Dataset preprocessing

EDA & data visualization

Communication

Team collaboration

Problem solving

Documentation

Education

Pursuing a degree in Computer Science / Electrical Engineering / Computer Engineering / Software Engineering / Aerospace Engineering / Math or related field

Tools

SQL

Python

R

Job description

Garmin is seeking a full-time Intern - Data Scientist at our Louisville, CO site. You will learn and train to develop large data sets, build ML models, and translate insights into actionable AI products.

Collaborate with cross-functional teams to drive data-driven decisions, design data pipelines, and monitor model performance while gaining hands-on experience in a leading tech company.