Data Analyst 2, Customer Complaints

Kenvue•Summit, NJ

4d•Onsite

About The Position

Kenvue is currently recruiting for a: Data Analyst 2, Customer Complaints What we do At Kenvue , we realize the extraordinary power of everyday care. Built on over a century of heritage and rooted in science, we’re the house of iconic brands - including NEUTROGENA®, AVEENO®, TYLENOL®, LISTERINE®, JOHNSON’S® and BAND-AID® that you already know and love. Science is our passion; care is our talent. Who We Are Our global team is ~ 22,000 brilliant people with a workplace culture where every voice matters, and every contribution is appreciated. We are passionate about insights, innovation and committed to delivering the best products to our customers. With expertise and empathy, being a Kenvuer means having the power to impact millions of people every day. We put people first, care fiercely, earn trust with science and solve with courage – and have brilliant opportunities waiting for you! Join us in shaping our future–and yours. For more information , click here . Role reports to: SR MGR GLOBAL CV SYSTEMS & TRENDING Location: North America, United States, New Jersey, Summit Work Location: Fully Onsite What you will do Data Analyst II plays a critical role in supporting the Global Complaint Vigilance (GCV) team by driving complex analytics initiatives and developing scalable solutions for global business partners. This role is embedded within a team that leads strategic efforts in Data Governance, Database Infrastructure, and Advanced Data Analytics for the Global Complaint platform.

Requirements

A minimum of a bachelor’s degree is required. A focus in Data Science/Engineering, or related field is preferred.
Proven experience in data analytics, preferably within a regulated or quality-focused environment.
Strong understanding of data lake architecture and data governance principles.
Proficiency in data querying, visualization, and statistical analysis tools.
Proficiency in Microsoft Power BI or equivalent data visualization tools
Excellent communication skills and ability to work across global teams and functions.
Power BI Development – dashboard creation, data visualization, and report automation.
DAX (Data Analysis Expressions) and Power Query for advanced data modeling and transformation.
SQL for querying and managing relational databases.
ETL (Extract, Transform, Load) processes for data integration and pipeline development.
Data Lake Architecture and Data Governance principles.
Python or R for statistical analysis and predictive modeling (as applicable).
Familiarity with Azure Data Services or other cloud-based data platforms.

Nice To Haves

Experience supporting manufacturing, packaging, and development operations is preferred.
Experience supporting aspects of the complaint vigilance life cycle for pharmaceutical, device, and /or cosmetic products is preferred.
Experience with one or more technologies supporting complaint handling preferred.
Expertise with root cause analysis techniques including but not limited to: Brainstorming, data analysis and collection tools, 5 Whys, Fishbone (Cause and Effect), FMEA, and DMAIC preferred.
Experience with tools and techniques supporting qualitative risk analysis including but not limited to: Probability and impact assessment (likelihood of recurrence and potential effect), probability and impact matrix (risk ratings, rating rules), and risk categorization (by root causes, other qualifiers) is preferred.
Experience with systems and tools supporting analysis and reporting preferred.

Responsibilities

Data Discovery & Ingestion : Support data analytics efforts by discovering relevant data within the Complaint Data Lake (CDL) and facilitating ingestion from source systems.
Stakeholder Collaboration: Partner with system owners to understand upstream processes and data inputs, ensuring alignment and data integrity.
Data Foundation Strategy : Lead initiatives to establish and maintain a robust data foundation in CDL, ensuring availability and curation of key quality data to support analytics and reporting needs.
Advanced Analytics Development: Design and implement innovative data science methodologies to support global metrics, trend analysis, and risk management planning.
Complaint Trend Analysis: Perform periodic analysis of complaint data to identify trends, risks, and opportunities for process improvement.
Cross-Functional Engagement: Collaborate with global stakeholders including Consumer Care Centers, Medical Safety, Business Quality, Marketing, Internal Affiliates, and External Sites to ensure consistency and compliance in the complaint vigilance process.
Training & Documentation: Assist in developing training materials and updating controlled documents related to complaint vigilance systems and processes.