Manufacturing Data Analyst

Agilent Technologies•North Kingstown, RI

6d•$58,800 - $91,875•Onsite

About The Position

This role partners with various teams including formulation, quoting, planning, scheduling, Product Data Management, and Quality Control to understand workflows, data requirements, and operational challenges. The Manufacturing Data Analyst will be responsible for collecting, organizing, cleaning, validating, analyzing, and maintaining manufacturing, laboratory, planning, quoting, and product data. This position supports daily scheduling and production workflows by preparing data, identifying gaps or discrepancies, and providing timely operational insights. The role involves developing and maintaining reports, dashboards, KPIs, data models, and analytical workflows to improve planning, resource utilization, and business continuity. Additionally, the analyst will facilitate process reviews, design future-state workflows, develop analytical models for various manufacturing processes, investigate data discrepancies, and translate business needs into technical specifications for software engineers. Support for LIMS and related systems, including configuration, master data setup, data mapping, testing, and training, is also a key responsibility. The role requires creating and maintaining documentation such as SOPs and user guides, providing hands-on support and training, and utilizing AI and advanced analytical tools responsibly to automate work and improve decision-making while ensuring data integrity and compliance with safety, quality, and controlled-document requirements.

Requirements

Bachelor’s degree in chemistry, biology, computer science, manufacturing technology, information systems, or a related field; equivalent relevant experience may be considered.
Ability to work full-time and 100% on-site in North Kingstown, Rhode Island.
Experience in a scientific laboratory, chemical production, manufacturing, or similarly technical environment.
Ability to understand and interpret laboratory and manufacturing data.
Strong attention to detail, documentation, organization, and problem-solving skills.
Comfort working with spreadsheets, structured data, and computer-based systems.
Working familiarity with artificial intelligence tools and an understanding of responsible use, output validation, data privacy, and appropriate human oversight.
Ability to work collaboratively with laboratory, manufacturing, quality, and technical teams.

Nice To Haves

Experience with LIMS, laboratory software, ERP systems, product data management systems, or manufacturing systems.
Experience with Excel, Power Query, Power BI, SQL, Python, Microsoft Fabric, Power Apps, or another analytical, programming, or low-code tool.
Experience using generative AI, machine learning, or AI-assisted analytical tools to support data preparation, analysis, documentation, automation, or workflow improvement.
Experience supporting software implementation, system testing, data migration, master data setup, or user training.
Experience designing repeatable analytical workflows, data models, or reporting standards.
Experience in a regulated manufacturing environment.
Familiarity with laboratory workflows, chemical formulations, sample tracking, specifications, quoting, planning, scheduling, or production documentation.

Responsibilities

Partner with formulation, quoting, planning, scheduling, Product Data Management, and Quality Control teams to understand workflows, data requirements, and operational challenges.
Collect, enter, organize, clean, validate, analyze, and maintain manufacturing, laboratory, planning, quoting, and product data.
Support daily scheduling and production workflows by preparing data, identifying gaps or discrepancies, and providing timely operational insights.
Develop and maintain repeatable reports, dashboards, KPIs, data models, and analytical workflows that improve planning, resource utilization, and business continuity.
Facilitate current-state process reviews and help design practical future-state workflows that reduce manual handoffs, strengthen data quality, and support continuous improvement.
Develop analytical models for production scheduling, raw material management, capacity planning, and other manufacturing workflows.
Investigate data discrepancies, determine root causes, and coordinate corrective actions with process owners and software engineers.
Translate manufacturing and business needs into clear data definitions, reporting requirements, system specifications, and user feedback for software engineers.
Support LIMS and related system configuration, master data setup, data mapping and migration, testing, validation, implementation, issue resolution, and user training.
Help design sustainable data structures, integrations, queries, automations, and reporting solutions that can scale with future site needs.
Create and maintain SOPs, work instructions, process maps, user guides, and controlled system documentation for new and existing workflows.
Provide hands-on support and training to manufacturing, laboratory, quality, and technical users following system or process changes.
Use AI and advanced analytical tools responsibly to automate repeatable work, identify patterns, and improve decision-making while validating outputs and protecting data integrity.
Perform all work in accordance with established safety, quality, data-integrity, and controlled-document requirements.