AI & Six Sigma Lead - Multiple Locations Available

Description

• Quality Management: Promotes accuracy, repeatability, and sustainment; avoids “AI for AI’s sake.”
• Publish simple, trustworthy metrics, dashboards, and playbooks that enable widespread use.
• Complete required training and achieve certification in the unified Six Sigma + AI curriculum; thereafter, when assigned, train and mentor, engineers, analysts, and other plant personnel in the methodology and tools.
• Advance the Autopilot Vision through digital twins, virtual Design of Experiments (DOEs), and multivariate process control, real-time optimization, predictive maintenance, and automated decisioning.
• Identify and automate routine/manual/transactional processes to reduce errors and cycle time and free talent for higher-value problem solving.
• Analytical: Interpret complex information; designs effective experiments and analyses.
• Ensure all solutions comply with applicable regulations, policies, and cybersecurity requirements.
• Lead change management to overcome adoption barriers; communicate progress and results clearly to all levels.
• Apply statistical methods and machine learning (e.g., time-series, regression/classification, anomaly detection, optimization) to uncover patterns across thousands of variables and augment human decision-making.
• Learn and apply robust data practices (quality, lineage, security) and Machine Learning Operations (MLOps) (versioning, validation, deployment, monitoring, retraining, rollback) to ensure safe and reliable model use.
• Change Leadership: Drives adoption across plants and corporate; removes barriers to scale.
• While performing the duties of this job, the employee may work around moving mechanical parts, at elevated heights, where dusts and fumes could be present in the air, with or in proximity to chemicals, in hot environments, around electrical equipment, and in a loud environment. The employee must have the ability to understand and mitigate these and other risks, including by following all prescribed safety rules, and must have the ability to wear appropriate personal protective equipment, if necessary.
• Execute assigned high-impact projects (provide input to charters as needed); manage scope, timeline, and stakeholders; track benefits and sustainment.
• Use LLMs to accelerate knowledge capture, interfaces to plant and corporate data, and workflow automation.
• Promote disciplined experimentation, Statistical Process Control (SPC), and hypothesis-driven problem solving.
• Collaborate across Operations, the Operations Center of Excellence, and Corporate Process Excellence to standardize, replicate, and scale proven solutions enterprise-wide.
• Lead projects using a combined Six Sigma method + AI playbook tightly aligned to plant and corporate priorities; deliver sustained, auditable value.
• Maintain documentation and change control consistent with TAMKO standards.
• Travel up to 15% to plants and corporate locations for discovery, implementation, training, and replication.
• While performing the duties of this job, the employee must be able to position himself/herself to operate, inspect, troubleshoot, repair, and/or maintain heavy plant equipment. This may require climbing stairs/ladders, bending, kneeling, crawling, squatting and/or stooping. The employee must frequently lift and/or move up to 10 pounds, occasionally lift and/or move up to 50 pounds, and may occasionally lift or move heavier objects with assistance.
• Project Management: Plans work, coordinates resources, manages risks, and delivers results.

Requirements

• Capable of learning new technical systems and using operational data. Manufacturing exposure is a plus, not a requirement.
• An understanding of the basics of building, deploying, and maintaining analytics/models and an eagerness to learn MLOps.
• Excellent communication skills; ability to translate technical insights for non-technical audiences and create clear reports, dashboards, and training materials.
• Proven ability to lead cross-functional teams and deliver results through influence and change leadership.
• Communication: Presents clearly; tailors messages for both technical and business audiences.
• Bachelor’s degree in Engineering, Computer/Data Science, Mathematics, or related STEM field; or equivalent combination of education and experience totaling 4–10 years of relevant experience in manufacturing/process improvement, data/analytics, or automation.
• Business Acumen: Aligns initiatives with strategy and value creation; measures impact.
• Problem Solving: Uses data and structured thinking to develop and evaluate alternatives.
• Technical Depth: Builds knowledge in AI/ML, statistics, data engineering, and industrial processes.

Benefits

Training + Development

Interview process

Visa Sponsorship

Security clearance