Qaulity Data Analyst

Prysmian•McKinney, TX

About The Position

Prysmian is the world leader in the energy and telecom cable systems industry. Each year, the Group manufactures thousands of miles of underground and submarine cables and systems for power transmission and distribution, as well as medium low voltage cables for the construction and infrastructure sectors. We also produce a comprehensive range of optical fibers, copper cables and connectivity for voice, video, and data transmission for the telecommunication sector. Everyone at Prysmian has the potential to make their mark; because whatever you do, wherever you are based, you will be part of a company that is helping transform the world around us. Make Your Mark at Prysmian! Objective Lead the transformation of Quality operations through the implementation of Artificial Intelligence (AI), advanced analytics, automation, and digital technologies that improve quality performance, accelerate decision-making, and enhance operational efficiency. Drive adoption of innovative solutions that reduce manual activities, improve problem-solving effectiveness, and create scalable systems that support continuous improvement and business growth. Scope Serves as the primary Quality resource for AI, digital innovation, analytics, and automation initiatives across manufacturing, engineering, and quality functions. Partners with Quality, Operations, Engineering, IT, and business leadership teams to identify opportunities where AI and digital technologies can improve operational performance, enhance quality systems, and support data-driven decision making. This position focuses on developing and deploying AI-enabled solutions, advanced analytics capabilities, automated workflows, intelligent reporting systems, and digital tools that support quality improvement, risk reduction, knowledge management, and process optimization across the organization.

Requirements

Artificial Intelligence & Digital Transformation: Ability to identify, develop, and implement AI-enabled solutions that improve quality performance, decision-making, and operational efficiency.
Data Analytics & Business Intelligence: Ability to analyze complex datasets, develop meaningful insights, and translate data into actionable business improvements.
Automation & Process Optimization: Experience developing automated workflows and digital solutions that improve productivity, reduce manual effort, and enhance process effectiveness.
Quality Improvement & Problem Solving: Knowledge of continuous improvement methodologies with the ability to drive sustainable quality and process improvements.
Project Leadership & Execution: Ability to lead cross-functional initiatives from concept through implementation while delivering measurable business results.
Change Management & Technology Adoption: Ability to influence stakeholders, promote digital innovation, and drive organizational adoption of new technologies and processes.
Communication & Collaboration: Strong communication, training, and stakeholder engagement skills with the ability to work effectively across multiple functions and organizational levels.

Responsibilities

Develop and implement AI-enabled solutions that improve quality performance, operational efficiency, and organizational decision making.
Identify, evaluate, and prioritize AI use cases that support quality inspections, root cause analysis, predictive quality monitoring, risk identification, and process optimization.
Deploy and support generative AI technologies, and digital assistants that enhance productivity and business effectiveness.
Design, develop, and maintain advanced quality analytics dashboards, KPI scorecards, and business intelligence reporting systems.
Leverage AI and analytics to identify trends, predict potential quality risks, and provide actionable recommendations to leadership.
Develop automated workflows utilizing Power Automate, Power Apps, and other digital platforms to eliminate manual processes and improve data accessibility.
Lead digital transformation projects from concept through implementation, adoption, and sustainment.
Support development of quality knowledge repositories, AI-powered knowledge bases, and intelligent search capabilities.
Collaborate with IT and business stakeholders to integrate quality data sources and establish scalable digital solutions.
Develop AI-assisted reporting and data analysis tools that improve visibility into COPQ, customer complaints, NCPs, audits, process performance, and operational metrics.
Monitor emerging technologies and evaluate opportunities to improve business performance through innovative digital capabilities.
Serve as the organizational champion for AI adoption and digital innovation within the Quality organization.