Sr. Analyst, Continuous Improvement Engineering

Description Hybrid 4 days on site in Burbank, CA Our client seeks a Senior Analyst, Continuous Improvement Engineering for a 12-week backfill to drive product-centric transformation and operational excellence. The role focuses on AI-first process reengineering, Lean Six Sigma methodologies, and measurable improvements across operations, engineering, and data functions. The analyst will design scalable solutions, optimize SLAs and KPIs, and ensure adoption through structured change management and capability building. Success requires analytical rigor, transformation leadership, and clear communication. Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance. Rate: $85.00 to $90.00/hr. w2 Responsibilities • Architect AI-first process reengineering strategies and redesign workflows for scalability and intelligence. • Integrate technologies such as Microsoft Copilot, predictive analytics, and generative AI to enhance decision-making and execution. • Develop AI agents to improve process and systems flow and drive automation. • Partner with cross-functional teams to design and pilot systems that identify and deliver high-impact automation opportunities. • Apply and govern AI-first process redesigns across core business processes. • Champion Lean Six Sigma to reduce waste and optimize end-to-end workflows. • Lead cross-functional initiatives using SIPOC, DMAIC, and Value Stream Mapping to improve quality and reduce defects. • Facilitate workshops, root cause analyses, and structured problem-solving sessions. • Drive improvements across software and hardware lifecycles to deliver product roadmaps. • Develop structured plans to assess, pilot, and scale innovative design and process solutions. • Create As-Is and To-Be process flows using tools such as Miro and Visio. • Leverage Agile and DevOps to drive iterative improvements and Sprint development. • Evaluate processes using interviews, workshops, Kaizen Events, process maps, and related tools. • Identify and communicate risks and issues impacting requirements and specifications. • Create training materials, SOPs, process maps, and design standards. • Define processes for technical platforms, specifications, and compatibility parameters. • Recognize structural issues and cross-silo redundancies to improve alignment. • Meet with leaders to scope opportunities, outline value and ROI, and identify risks and constraints. • Develop and deliver Lean Six Sigma training programs to foster continuous improvement. • Mentor teams through structured learning, coaching, and experiential learning. • Promote PDCA and agile experimentation for iterative improvement. • Combine Lean Six Sigma and change management frameworks to prepare for and measure future state. • Define and operationalize SLAs and KPIs aligned to strategic goals. • Conduct post-implementation reviews and success audits. • Analyze datasets for trends, create reports, forecasts, and recommendations. • Utilize Power BI or Tableau for data extraction and visualization, including ERP data sources. • Develop plans for data collection, management, and usage to meet customer needs and SLAs. • Define shared data elements and relationships across business units. Experience Requirements • 5+ years of process improvement or quality experience. • Lean Six Sigma certified. • Experience in Agile, DevOps, and Sprint development. • Familiarity with AI or ML techniques in manufacturing such as predictive maintenance, anomaly detection, and process mining. • Experience with ITIL or CMMI. • Project management experience such as PMI or PRINCE2. • Experience with ADKAR change management frameworks. • Ability to work in an ambiguous environment and collaborate across functions. • Strong interpersonal, analytical, and communication skills with the ability to influence without authority. • Ability to interpret business issues, recommend best practices, and identify innovative solutions. Education Requirements • Bachelor’s degree in Computer Science, Industrial Engineering, Mechanical Engineering, or a comparable field, or equivalent work experience.