Data, Analytics & AI Internship — Remote Fridays

ADT; Boca Raton (FL); Hybrid; USD 33,000 - 39,000; Full time

Benefits offered by this job

LinkedIn Learning access

ELT Speaker Series

Diversity and inclusion initiatives

Volunteer opportunities

Job summary

ADT Data, Analytics & AI Internship in Boca Raton Headquarters offers an 11-week program with in-person learning Monday–Thursday and remote Fridays. Compensation is $24/hour for Bachelor's students and $28/hour for Master's students. Dates are May 17–July 29, 2027, with on-site work and team-based projects.

Interns will gain exposure to multiple ADT business units, participate in professional development, and contribute to data pipelines, dashboards, analyses, and AI/ML initiatives.

Qualifications

• Pursuing a Bachelor's or Master's degree in Data Science, Computer Science, Business Analytics, Statistics, Mathematics, Information Systems, AI, or related field
• Graduating between Dec 2027 and May 2028
• Completion of at least two upper-level (300/400) courses relevant to the internship discipline
• Cumulative GPA of 3.2 or higher
• Applicants must be authorized to work for any employer in the U.S. without sponsorship

Responsibilities

• Work on data pipelines and data infrastructure projects
• Develop dashboards and reporting solutions
• Analyze business and customer data to identify insights
• Support AI/ML initiatives and data-informed decision making

Skills

Analytical thinking

Communication

Problem solving

Collaboration

Leadership

Education

Pursuing BS/MS in Data Science/CS/Analytics

Tools

SQL

Python

R

Tableau

Power BI

Job description

ADT Data, Analytics & AI Internship in Boca Raton Headquarters offers an 11-week program with in-person learning Monday–Thursday and remote Fridays. Compensation is $24/hour for Bachelor's students and $28/hour for Master's students. Dates are May 17–July 29, 2027, with on-site work and team-based projects.

Interns will gain exposure to multiple ADT business units, participate in professional development, and contribute to data pipelines, dashboards, analyses, and AI/ML initiatives.