Overview Do you want to join a team that's changing the world? Do you have a strong background as a Sr. Engineer, Industrial AI and Analytics? Then we're looking for you! Check out the job description and apply now! Put your skills to meaningful use, gain unique experience, and work with world-class team members with diverse backgrounds and expertise who share the same vision. Join the PECNA team today! Responsibilities Sr. Engineer, Industrial AI and Analytics https://www.youtube.com/watch?v=0tMgKm_71qs (by clicking this link you are being referred to an external site that is not part of Panasonic) Meet the Recruiter: Princess Damato Job Summary: Panasonic Energy is seeking a Sr. Engineer, Industrial AI and Analytics reporting to the Sr. Director, Next Gen Initiatives. This role operates within the Next Gen Initiatives (NGI) team, a strategic function responsible for advancing automation, AI enablement, and operational transformation across PECNA. This role focuses on the digital and systems execution layer of manufacturing: deploying analytics, industrial AI, data products, and decision-support tools that improve how manufacturing teams see, decide, and act. The engineer will drive deployment of factory intelligence platforms, operational dashboards, AI/ML solutions, digital twin/simulation concepts, command-center capabilities, and AI-enabled decision support. This role converts Next Gen concepts into production-ready digital capabilities that improve safety, quality, productivity, throughput, and cost performance. The ideal candidate blends future-forward curiosity with a hands-on approach to problem-solving. You will translate complex manufacturing challenges into structured initiatives, driving cross-functional execution from early discovery and ideation through proof-of-concept and full deployment, ensuring measurable performance improvements and sustained adoption across the shop floor. Essential Duties: Strategy & Execution Partner with site leadership and manufacturing stakeholders to define and prioritize analytics, digital AI, and production systems initiatives aligned to NGI pillars and identify opportunities to improve performance, cost, and workforce capability. Translate operational challenges into clear initiative charters and drive end-to-end delivery across digital systems (analytics/AI). Own use cases from discovery through proof of concept to scaled deployment, ensuring solutions are operationally relevant, explainable, and embedded into frontline workflows. Manage initiative timelines, risks, and dependencies; drive issue resolution with cross-functional stakeholders. Next Gen Technologies Evaluate, pilot, deploy emerging analytics and digital AI technologies across production sites, including industrial data platforms, AI/ML solutions, digital twins, command centers, and agentic/GenAI tools. Identify and evaluate high-impact opportunities in areas such as predictive maintenance, quality prediction, SPC automation, process optimization, yield improvement, and decision support. Identify and prioritize analytics and digital AI opportunities that deliver measurable improvements in productivity, throughput, quality, and cost performance. Partner with Operations, Process Engineering, Quality, Maintenance, IT/OT, SCADA/MES, and data teams to convert manufacturing data into reliable, governed data products, dashboards, and decision-support tools. Develop evaluation frameworks to assess readiness, data quality, usability, security, reliability, scalability, and ROI before scaled deployment. Stakeholder & Vendor Coordination Bridge the gap between Operations, Engineering, Safety, Maintenance, DataX, Quality, Finance, HR, and Supply Chain to ensure digital deployments are secure, scalable, adopted, and sustainable. Drive deployment of Nevada tools to Kansas. Manage relationships with data/AI platform partners, systems integrators, and analytics vendors, including requirements, delivery milestones, validation, and performance accountability. Define and track KPIs such as data quality, adoption, uptime/availability, throughput, yield/quality, cost performance, workflow efficiency, and ROI. Document standards, data definitions, workflows, and best practices to enable repeatable digital deployment across NV and KS sites. Support training and change management for sustainable ownership by relevant teams. Personal Protective Equipment (PPE) Requirements: To ensure health and safety in the workplace and for employee protection, wearing PPE is required and includes equipment such as a full Tyvek suit, safety shoes, gloves, safety glasses, face mask, and a full hazmat suit that includes a respirator. A respirator fit test will be required based on functional area. The foregoing description is not intended and should not be construed to be an exhaustive list of all responsibilities, skills and efforts or work conditions associated with the job. It is intended to be an accurate reflection of the general nature and level of the job. Qualifications Requirements - Required and/or Preferred Required Education, Certifications, and Licenses: Bachelor's degree in Engineering, Data Science, Industrial Engineering, Computer Science, Information Systems, or related field Preferred Education, Certifications, and Licenses: Master's degree in a related field PMP, Palantir Foundry certification, or equivalent continuous improvement / digital platform certification Essential Qualifications: 7+ years of experience in manufacturing analytics, industrial data systems, production systems, digital transformation, applied AI/ML, or systems integration within a high-volume manufacturing environment. Proven cross-functional delivery from concept to adoption. Knowledge of factory systems (MES, SCADA, PLCs, ERP, CMMS, SPC) and how they interconnect to support analytics and decision-making. Experience building or managing delivery of operational dashboards, data pipelines, data products, analytics applications, or AI-enabled tools. Strong communication, structured problem-solving, and stakeholder management skills. Strong project execution skills with ability to manage scope, timeline, risks, dependencies, adoption, and cross-functional stakeholders. Strong communication skills, comfortable working on the shop floor with operations and presenting progress to leadership. Preferred Qualifications: Experience in battery, semiconductor, automotive, pharmaceutical, or high-speed consumer goods manufacturing Experience with one or more programming, scripting, or data development languages such as Python, SQL, JavaScript, C#, Java, R, or similar tools used for analytics, automation, application development, or systems integration. Experience with industrial analytics platforms, Palantir Foundry or similar tools, operational dashboards, digital twins, predictive maintenance, quality analytics, or command-center capabilities Hands-on experience using modern large language models and GenAI tools such as Claude, Gemini, ChatGPT, Microsoft Copilot, or similar platforms to improve productivity, automate workflows, support data analysis, or develop AI-enabled business and manufacturing solutions. Familiarity with industrial data architecture, Industrial Data Fabric, Unified Namespace, OT cybersecurity, OPC-UA/DA, MQTT, Modbus, or related data integration concepts Experience with Lean, Six Sigma, TPM, analytics adoption, data governance, or continuous improvement methodologies Experience working with Japanese manufacturing partners or in cross-cultural engineering environments Travel Requirement: Up to 25% travel required Physical Demands: Physical Activities: Percentage of time (equaling 100%) during the normal workday the employee is required to: Sit: 50% Walk: 30% Stand: 20% Required Lifting and Carrying: Rare (