UDI Data Steward & Labeling Analyst

Experis (Austria); Plymouth (MN); On-site; USD 39,000 - 41,000; Full time

Benefits offered by this job

Medical and Prescription Drug Plans

Dental Plan

Vision Plan

Health Savings Account

401(k) Plus Match

Weekly Pay

Job summary

ManpowerGroup, the leading global workforce solutions company, seeks a Data Management Analyst / Labeling Specialist to support UDI master data and regulatory data in Plymouth, MN. The role emphasizes accuracy, cross-functional collaboration, and adherence to deadlines within IT systems.

You will contribute to data integrity and regulatory compliance, performing analyses and audits while coordinating with multiple teams to resolve data and labeling issues.

Qualifications

• 2+ years of experience in data management, data analysis, or master data processes.
• Experience working with IT systems and databases.
• Ability to manage multiple projects and priorities simultaneously.
• Strong problem-solving and organizational skills.
• Verbal and written communication across teams.

Responsibilities

• Create, maintain, and manage UDI master data and workflows within internal IT systems.
• Perform data analysis and audits to ensure compliance with global UDI regulations.
• Support cross-functional teams by maintaining accurate labeling and regulatory data.
• Assist in identifying, troubleshooting, and resolving business data and technical issues.
• Manage multiple concurrent assignments while meeting established deadlines and project timelines.

Skills

Data management

Data analysis

Master data processes

IT systems

Communication

Job description

ManpowerGroup, the leading global workforce solutions company, seeks a Data Management Analyst / Labeling Specialist to support UDI master data and regulatory data in Plymouth, MN. The role emphasizes accuracy, cross-functional collaboration, and adherence to deadlines within IT systems.

You will contribute to data integrity and regulatory compliance, performing analyses and audits while coordinating with multiple teams to resolve data and labeling issues.