Key Responsibilities

Enterprise AI & Advanced Analytics Solutions

• Design, develop, and deploy AI- and machinelearningenabled solutions that leverage manufacturing data to:

• Accelerate root cause identification

• Predict quality, waste, and equipment failure mechanisms

• Improve speed, consistency, and effectiveness of problem solving

• Focus onstandard, repeatable solutionsthat can be implemented across multiple plants rather than oneoff, sitespecific tools

• Applyreal world process knowledgeto ensure analytical outputs align with real failure mechanisms and actionable countermeasures

Manufacturing Data Architecture & Integration

• Partner with Automation and IT teams to:

• Connect machine and process data through systems such as Ignition

• Establish standardized, reliable data pipelines and flows

• Reduce manual data collection and fragmented data sources

• Develop a working understanding of Shaws manufacturing data infrastructure and data sources relevant to Residential Manufacturing

• Apply discretion and judgment in selecting appropriate data, models, and technologies to meet business needs

Problem Solving Enablement & Capability Building

• Enable plant engineering and operations teams to:

• Improve data literacy related to process and machine data

• Understand how AIdriven insights support root cause analysis

• Begin developing and sustaining their own impactful analytics solutions over time

• Develop and deliver training materials, bestpractice guides, and coaching to increase engagement and adoption

• Build analytical solutions that are transparent, trusted, and usable by manufacturing teamsnot black boxes

Visualization, Adoption, and Business Impact

• Develop purposebuilt visualizations, dashboards, and reports that clearly communicate insights, drivers, and recommended actions

• Apply best practices in visualization design to support fast, confident decisionmaking by manufacturing leaders

• Track adoption, utilization, and business impact of deployed solutions

• Identify gaps in tools, data, or capability and proactively address them to improve outcomes

Qualifications & Experience

Required

• Bachelors Degree (Engineering preferred)

• Manufacturing engineering experience with strong understanding of production processes and equipment behavior

• Demonstrated experience using manufacturing data to solve operational problems

• Experience working with industrial data systems and historians (e.g., Ignition, OPC data)

• Ability to independently learn and apply new analytical techniques, tools, and programming languages

Preferred

• Experience with advanced analytics, machine learning, or predictive modeling in a manufacturing environment

• Experience with tools and technologies such as:

• Ignition, SQL-based databases, Python

• BI and visualization tools (e.g., Qlik, Tableau, Power BI)

• Experience working across multiple facilities or in an enterprise manufacturing role

• Familiarity with quality, waste, and equipment performance improvement methodologies

Core Competencies

• BuildCustomerSatisfaction Builds trust and alignment with plant and functional leaders

• Innovate Appliesnew technologythoughtfully to real manufacturing challenges

• LearnContinuously Continuously develops technical, analytical, and business skills

• InfluenceOthers Leads throughexpertiseand partnership rather than authority

• Execute Action Plan Delivers practical solutions with clear business impact