Job Description
Job Summary
This position will contribute to Continuous Improvement under the COS (Carlisle Operating System) structure through advancement of Lean Six Sigma methodology, data-driven problem solving, and practical applications of artificial intelligence. The role involves leading and supporting DMAIC(Define → Measure → Analyze → Improve → Control) and DMADV (Define à Measureà Analyze à Design à Verify) projects, as well as A3/5Cs, while working closely with cross-functional teams to improve processes, strengthen decision making, and identify scalable opportunities for operational excellence.
The individual will serve as a strategic problem solver who can translate complex business and operational challenges into structured analytical approaches, whether through process redesign, decision support tools, automation, advanced analytics, or selective application of AI capabilities. Rather than focusing solely on model development, this role plays a key part in helping the organization determine where AI and analytics can create meaningful value, where traditional improvement methods remain most appropriate, and how to embed these capabilities into day-to-day decision making.
By developing dashboards, analytical frameworks, decision-support tools, and AI-enabled workflows, this position plays a vital role in fostering a data-driven culture of continuous improvement and supporting the transition from descriptive analytics to predictive, prescriptive, and more intelligent operational decision making.
Duties and Responsibilities:
Analyze business processes, workflows, and operational challenges to identify opportunities where AI, automation, or advanced analytics can improve efficiency, decision making, or performance.
Work with cross-functional teams (quality, operations, engineering, supply chain, sales, customer service) to understand current workflows, bottlenecks, and decision gaps.
Evaluate identified problems using structured thinking to determine the most appropriate solution approach (process improvement, analytics, automation, or AI-based augmentation).
Build and maintain an “AI opportunity pipeline” by documenting, categorizing, and prioritizing use cases based on impact, feasibility, and alignment with business needs.
Develop lightweight prototypes and proof-of-concepts (e.g., dashboards, simple models, GenAI workflows, automation scripts) to test and demonstrate the value of identified opportunities.
Assist in translating validated opportunities into practical solutions, including simple tools, workflows, or decision-support systems that can be used by stakeholders.
Support implementation of AI-enabled or analytics-driven solutions in operational environments, ensuring usability, clarity, and alignment with existing processes.
Create clear visualizations, summaries, and presentations that communicate both the opportunity and the results of prototypes or pilots to stakeholders.
Translate ambiguous business challenges into structured problem statements, hypotheses, and testable solution approaches.
Research and experiment with emerging AI tools and techniques (e.g., generative AI, workflow automation, intelligent search) and apply them to real business use cases.
Assist in evaluating the impact of implemented solutions, including measuring performance improvements, identifying limitations, and recommending next steps.
Support Lean & Six Sigma initiatives by identifying where AI and advanced analytics can enhance, accelerate, or complement traditional DMAIC/DMADV approaches.
Document use cases, learnings, and best practices to help build organizational knowledge around effective application of AI in operations.
Required Knowledge/Skills/Abilities:
Essential Knowledge
Basic understanding of Lean and Six Sigma principles and structured problem-solving approaches
Basic knowledge of data analytics, AI concepts, and practical applications of automation, generative AI and agentic AI.
Familiarity with MS Office and exposure to data analysis tools (e.g., Excel, Python, SQL, or similar)
Essential Skills:
Strong critical thinking and structured problem-solving ability
Ability to break down ambiguous business problems into clear, actionable components
Basic proficiency in data analysis, visualization, and interpretation
Ability to evaluate different solution approaches (process improvement, analytics, automation, AI) and understand tradeoffs
Effective written and verbal communication skills
Ability to learn and apply new tools and technologies quickly
Time management and ability to manage multiple tasks or workstreams
Essential Abilities:
Strong degree of initiative and self-motivation
Curiosity in identifying problems, inefficiencies, and opportunities for improvement
Ability to connect business context with analytical or AI-driven solutions
Willingness to challenge assumptions and think beyond existing processes
Strong follow-up/follow through
Adaptability in working with evolving tools, technologies, and problem spaces
Ability to take ownership of small scoped projects from idea through prototype and validation
Education and Experience:
Required:
Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field from a four-year college or university
2+ years’ experience with related operation/business functions
Working Conditions:
Office environment setting with occasional plant settings where the plants may be dirty dusty and hotter/colder than office settings.
Monday – Friday; 8:00 am – 5:00 pm