No Relocation Assistance Offered
Job Number #173962 - Topeka, Kansas, United States

Who We Are

Colgate-Palmolive Company is a global consumer products company operating in over 200 countries specializing in Oral Care, Personal Care, Home Care, Skin Care, and Pet Nutrition. Our products are trusted in more households than any other brand in the world, making us a household name!

Join Colgate-Palmolive, a caring, innovative growth company reimagining a healthier future for people, their pets, and our planet. Guided by our core values—Caring, Inclusive, and Courageous—we foster a culture that inspires our people to achieve common goals. Together, let's build a brighter, healthier future for all.
 

 

The Specialist/Sr. Specialist, Quality Data & Insights transforms global consumer and veterinary complaint data into actionable intelligence to elevate product quality and pet parent trust. This role ensures compliance by extracting, validating, and evaluating data from global systems (e.g., Wilke-Global, CRS, SAP), overseeing complaint and adverse event investigations, and ensuring timely closure per quality and regulatory standards. The position improves traditional monitoring through automated early-warning systems, predictive watch lists, and Production Run Alerts (PRA) to identify and escalate emerging quality risks. This role designs and maintains robust data models and infrastructure, enabling fast, data-informed decisions. This role partners cross-functionally to align data architecture with business needs, supports complaint-proof design for new product launches, and leads monthly complaint review forums, translating complex findings into concise, impactful insights for all stakeholders.

 

Responsibilities:

Data Management, Integrity and Compliance

• Extract data from global databases (Wilke-Global, CRS database), maintain tracking tables, review data for accuracy, and close adverse event complaints.

• Lead oversight of consumer complaint investigations and ensure completion per quality and regulatory requirements.

• Provide monthly complaint reports to plants and contract manufacturers (Comans) and support audits and regulatory visits (e.g., FDA).

• Update complaint Standard Operating Procedures (SOP).

Advanced Trend Intelligence & Alerts

• Elevate traditional complaint monitoring by developing automated early-warning systems.

• Maintain a predictive "Watch List" to identify emerging consumer trends and monitor complaint metrics, enabling proactive intervention before market impact.

• Manage the identification of high-risk issues exceeding established thresholds to generate Production Run Alerts (PRAs) and deliver ad hoc reports on various complaint metrics.

• Data Engineering & Infrastructure.

• Use data analytics platforms to design and aggregate consumer and veterinary complaint data.

• Transform raw data from global databases and SAP into well-documented, actionable data models for the Quality organization.

Cross-Functional Collaboration & Investigation

• Partner with cross-functional stakeholders to align data architecture with business needs.

• Provide data-driven support during the process to ensure new product launches are designed to minimize consumer complaints and maximize product superiority from Day 1. Support Root Cause Analysis efforts with cross-functional teams.

Executive Communication, Reporting & Meetings

• Lead monthly complaint review meetings (including Quality, Supply Chain, Marketing, Legal, and S&T).

• Communicate technical analytical concepts to non-technical stakeholders and departmental leadership in a compelling manner, driving a culture of data-informed decision-making and clear, actionable outcomes.
  
  

Required Qualifications:

• Bachelor's degree in Business, Economics, Statistics, Mathematics, Engineering, Data Science, Computer Science, Marketing, or a related field.

• 4+ years of experience in performing and applying data analysis/analytics, compliance, risk management or quality control.

• Experience with querying, cleaning, and integrating datasets from multiple sources, building and using pivot tables, and creating cu