GenAI/ML Intern — Hybrid Role Focused on Data & ML Projects

American Family Insurance; Boston (MA); Hybrid; USD 52,000 - 108,000; Full time

Job summary

American Family Insurance is seeking an intern to assist in building ML applications and supporting IT and software projects at our Madison, WI base. You will work under supervision to develop and analyze data-driven solutions while adapting to changing team needs and business priorities.

You should be enrolled full-time in an accredited degree program and have completed foundational coursework in computer science or related fields.

Qualifications

• Enrolled full-time in a bachelor’s, master’s, or doctoral degree.
• Must have completed 24 semester hours prior to first work term.
• Preferred programs: Computer Science, Computer Engineering, Software Engineering, Data Science, AI.

Responsibilities

• Assist in establishing and maintaining strategies to meet organizational objectives.
• Develop an understanding of the business environment and culture to support initiatives.
• Build and develop ML applications to address business problems.
• Data cleaning, preparation, and analysis.
• Participate in projects related to application support, software development, IT operations, system enhancements, and technology solutions.
• Present project results to management.
• Stay updated on quantum computing, ML, and emerging tech trends.

Skills

Analytical skills

Problem-solving

Communication skills

Customer service

Data analytics

Python

ML frameworks

Education

Bachelor’s/Master’s/Doctoral degree (pursuing)

24 semester hours completed

Tools

Python

ML frameworks

SQL

Job description

American Family Insurance is seeking an intern to assist in building ML applications and supporting IT and software projects at our Madison, WI base. You will work under supervision to develop and analyze data-driven solutions while adapting to changing team needs and business priorities.

You should be enrolled full-time in an accredited degree program and have completed foundational coursework in computer science or related fields.