Tech Co-op: Data Analytics & Automation (GenAI)

Johnson & Johnson Innovative Medicine; Raritan (NJ); Hybride; USD 36 000 - 47 000; Plein temps

Avantages offerts par ce poste

Housing stipend

Résumé du poste

Johnson & Johnson is seeking a JJT Co-op in Technology Leadership Development Program (TLDP) for Spring 2027 in a hybrid role based in Raritan, New Jersey. The six-month Co-op (March 29, 2027 – August 20, 2027) offers deep exposure to data analytics, automation, and collaboration across teams.

You will work 40 hours per week, performing data analysis, contributing to automation efforts, and supporting CSI initiatives within Innovative Medicine and MedTech spaces.

Qualifications

• U.S. work authorization is required for all applicants.
• GPA of 3.0 or higher is required across college coursework.
• Currently enrolled pursuing a bachelor’s or master’s degree; major in Information Management, IT, CS, or related field preferred.

Responsabilités

• Perform data analysis on structured and unstructured data sets to uncover insights for process improvements.
• Be involved in Application Maintenance critical initiatives.
• Drive automations to improve reliability, quality, and lower costs using JNJ automation and GenAI tools.
• Standardize and automate daily processes and checks.
• Enable collaborative data analysis and ensure data quality.
• Identify CSI opportunities and deliver improvements.

Connaissances

Python data science libraries

ML tools & algorithms

GenAI technologies

GenAI models (MCP & Agentic frameworks

Agile & Scrum

Collaboration skills

Independent work & multi-priority

MS Office

Formation

Pursuing Bachelor’s or Master’s degree

Outils

MS Office

Description du poste

Johnson & Johnson is seeking a JJT Co-op in Technology Leadership Development Program (TLDP) for Spring 2027 in a hybrid role based in Raritan, New Jersey. The six-month Co-op (March 29, 2027 – August 20, 2027) offers deep exposure to data analytics, automation, and collaboration across teams.

You will work 40 hours per week, performing data analysis, contributing to automation efforts, and supporting CSI initiatives within Innovative Medicine and MedTech spaces.