Regional Lean Business Analyst, Operational Excellence

Agilent Technologies•Santa Clara, CA

4d•Onsite

About The Position

The Regional Lean Business Analyst is a deployment-embedded role, not a desk-based reporting function. You will spend significant time on manufacturing floors alongside the RDL and Lean Manufacturing Specialist during site diagnostics and improvement cycles, directly observing processes, engaging with production teams, and gathering the data to turn into action. During active deployments, the Regional Lean Business Analyst works under the direction of the Regional Deployment Leader as part of the integrated triad. What makes this role distinct is the combination of genuine lean deployment experience with the analytical capability to substantiate what the team finds on the floor. You need to understand what you are looking at on the floor before you can structure the data behind it. The right candidate is someone who has led or participated meaningfully in lean or continuous improvement deployments and brings enough technical fluency to build the tools, dashboards, and tracking mechanisms that make improvement outcomes visible and defensible.

Requirements

Bachelor’s degree in Industrial Engineering, Manufacturing Engineering, Data Science, Business Analytics, or a related quantitative discipline.
8+ years of professional experience in manufacturing operations with direct, hands-on involvement in lean or continuous improvement deployments, kaizen events, or structured operational improvement programs at the floor level.
Strong analytical and data fluency with demonstrated ability to build and apply tools such as Python, Power BI, or equivalent platforms for data manipulation, visualization, and operational analysis.
Experience extracting and working with data from ERP systems (SAP strongly preferred) and manufacturing execution systems.
Working knowledge of project management tools such as Jira, Smartsheet, or equivalent, with experience tracking multi-workstream improvement programs.
Comfort operating in a manufacturing floor environment during deployments, including direct interaction with production operators, supervisors, quality engineers, and site planners.
Strong written and verbal communication skills, with the ability to distill complex operational and analytical findings into clear narratives for both technical and executive audiences.
Willingness to travel 30–50% within the Americas region during active deployment periods.
Occasional international travel for cross-regional collaboration.

Nice To Haves

Experience in regulated manufacturing environments such as life sciences, diagnostics, or pharmaceuticals.
Direct experience operating within a structured production system methodology such as the Toyota Production System, Danaher Business System, or comparable enterprise-wide operational excellence framework, with an understanding of how deployment-based improvement differs from project-based continuous improvement.
Working familiarity with manufacturing cost structures, standard costing, and the mechanics of how operational improvements translate to financial outcomes at the site level.
Experience with SQL for direct database queries and data extraction.
Exposure to both instrument manufacturing and biological or pharmaceutical manufacturing environments.
Master’s degree in a relevant quantitative field.

Responsibilities

Deploy on-site alongside the RDL and Lean Manufacturing Specialist during diagnostic and improvement cycles at Americas manufacturing sites, serving as the analytical backbone of the deployment trio.
Participate and conduct direct floor-level process observation, time studies, material and information flow analysis, and Gemba-based problem identification as an active member of the deployment team.
Translate floor-level observations into structured problem statements and quantified opportunity assessments that the triad uses to prioritize improvement efforts with site leadership.
Support the design and implementation of lean countermeasures including standard work development, visual management systems, pull-based material flow, and quality process improvements in collaboration with site teams.
Contribute to diagnostic synthesis documents, deployment readouts, and site leadership presentations that communicate findings, recommendations, and results clearly and credibly.
Gather, clean, and structure production, quality, planning, and logistics data from site systems (SAP, MES, LIMS, and local databases) to support deployment diagnostics and ongoing improvement tracking.
Build analytical models and dashboards using tools such as Python, Power BI, or equivalent platforms that help the deployment team identify process bottlenecks, capacity constraints, yield losses, and planning gaps.
Develop tracking mechanisms and visual reporting that replace manual processes with clear, real-time visibility into deployment progress and site performance.
Manage deployment project tracking through Jira or equivalent tools, maintaining clear visibility into action item status, ownership, timelines, and completion evidence across concurrent site engagements.
Partner with site controllers and the OEX control tower to substantiate improvement outcomes using the OEX Value Recognition Framework, ensuring savings claims are categorized accurately and supported by verifiable evidence.
Prepare financial impact summaries for deployment readouts and leadership reporting, translating operational improvements into the gross profit recovery and cost reduction language that the organization tracks.
Build and maintain regional tracking tools that provide cumulative visibility into the Americas deployment portfolio, savings trajectory, and site maturity progression.
Develop reusable analytical templates, diagnostic data request packages, and deployment playbooks that accelerate future site engagements and reduce the ramp-up time for new team members.
Train site-level personnel on basic data collection protocols and self-service reporting tools so that improvement visibility persists after the deployment team transitions out.
Contribute to the evolution of OEX’s analytical methodology, incorporating new tools and emerging best practices as the function matures.