Data Analytics Intern: Build Insights from Medical Data

F39055 OEC Medical Systems, Inc.; Salt Lake City (UT); On-site; USD 25,000 - 39,000; Full time

Job summary

GE HealthCare in Salt Lake City is seeking a Data Analytics Intern to turn real-world data into actionable insights. You will build Power BI dashboards, analyze data from SQL Server, Excel and cloud platforms, and collaborate with field ops managers, clinical engineers, and data scientists to define KPIs and reporting needs.

You will apply AI models to detect patterns, develop predictive tools to optimize dispatching and downtime, and support ad-hoc data projects in a fast-paced environment.

Qualifications

• Pursuing or recently completed CS/Data Science/IS degree.
• Experience with data warehousing/preparation or data gateways.
• Hands-on with Microsoft BI stack (Power BI, SSAS, SSRS, SSIS) including DAX/Power Query.
• Understanding of JavaScript, CSS, SQL; Python or R preferred.
• Experience with biomedical data or web apps is a plus.

Responsibilities

• Build interactive Power BI dashboards to visualize device performance and service metrics.
• Analyze data from SQL Server, Excel, and cloud platforms to uncover patterns.
• Collaborate with field ops managers, clinical engineers, and data scientists to define KPIs.
• Automate reporting workflows with Power Automate and Power Apps.
• Present insights to cross-functional teams and support strategic discussions.
• Apply AI models to identify patterns signaling inefficiencies or failures.
• Develop predictive tools to optimize technician dispatching and reduce downtime.

Skills

Power BI

SQL

Python

R

Data visualization

Machine learning basics

JavaScript

CSS

Education

CS / Data Science / IS degree

Tools

SSAS

SSRS

SSIS

DAX

Power Query

Power Automate

Power Apps

Job description

GE HealthCare in Salt Lake City is seeking a Data Analytics Intern to turn real-world data into actionable insights. You will build Power BI dashboards, analyze data from SQL Server, Excel and cloud platforms, and collaborate with field ops managers, clinical engineers, and data scientists to define KPIs and reporting needs.

You will apply AI models to detect patterns, develop predictive tools to optimize dispatching and downtime, and support ad-hoc data projects in a fast-paced environment.