Labeling Data and Quality Analyst

Overview

Audit and validate labeling annotation data, investigate quality errors and drive process improvements for Kenvue's global R&D labeling operations.

What you'll do

• Audit and validate labeling annotation data for accuracy, consistency and guideline adherence.
• Identify, document and report errors and root cause triggers to management and stakeholders.
• Monitor quality KPIs (Right First Time rates, rework triggers) and drive monthly governance cycles.
• Translate data trends into actionable process improvement plans across agencies and internal teams.
• Ensure compliance with regulatory and safety requirements throughout the labeling process.
• Lead the NC Program.

What you'll need

• Bachelor's degree in a relevant field or equivalent experience in Data Science/Computer Science.
• 2–4 years of experience in data analytics, root-cause analysis, or quality assurance.
• Relevant experience in FMCG, Pharma, or Healthcare domains.
• Strong analytical skills with proficiency in Analytics and Visualization, ETL and Data Engineering.
• Proficient in PowerBI, Python and Data Modeling techniques.
• Excellent communication skills across stakeholder levels.

Nice to have

• Experience working with APAC and/or EMEA markets.
• Experience with AI data preprocessing, building agents, Power Platform.
• Familiarity with labeling annotation tools and processes.

Details

• Reports to: Project Leader - Global R&D Systems.
• Location: Asia Pacific, India, Maharashtra, Greater Mumbai.
• Work mode: Hybrid.