Specialist, Data Analytics

JD_Specialist Data Analyics

Transform manufacturing data into clear insights that improve safety, quality, delivery, cost, and people outcomes. Build trusted dashboards and analytical models, maintain common KPI definitions, identify performance gaps and root causes, and partner with plant and functional teams to convert insights into measurable improvement actions. Support the Data Excellence Manager in delivering strategic projects and building a scalable, trusted data foundation for manufacturing.

Key responsibility Manufacturing Performance Analytics

• Analyze production, quality, maintenance, material, labor, capacity, and cost data to identify trends, losses, constraints, and improvement opportunities.
• Perform root-cause, variance, correlation, forecasting, and scenario analyses to support operational and strategic decisions.
• Translate analytical findings into concise recommendations for plant leaders and Manufacturing Excellence stakeholders.

Strategic Projects and Data Foundation

• Support the Data Excellence Manager in planning and delivering strategic Manufacturing Excellence data and analytics projects.
• Provide data analysis, requirements gathering, testing, documentation, benefit tracking, and implementation support across the project lifecycle.
• Build and maintain the manufacturing data foundation, including common data models, KPI logic, data dictionaries, metadata, master data rules, lineage, and quality controls.
• Help connect and harmonize data across plants, functions, and source systems to enable trusted reporting, advanced analytics, and future AI use cases.

Dashboards and Reporting

• Develop and maintain Power BI dashboards, data models, and standard reports for manufacturing performance.
• Automate recurring data preparation and reporting to improve speed, consistency, and traceability.
• Monitor dashboard adoption and improve usability based on stakeholder feedback.

KPI and Data Standardization

• Maintain common definitions and calculation logic for manufacturing KPIs such as OEE, yield, scrap, downtime, cycle time, WIP, productivity, capacity, and plan versus actual.
• Support data dictionaries, master data rules, metadata, lineage, and access requirements.
• Validate source data and resolve data-quality issues with data owners and system teams.

Business Partnering and Improvement

• Work with production, engineering, quality, maintenance, planning, finance, and digital teams to clarify business questions and analytical requirements.
• Support improvement projects with baseline analysis, benefit tracking, and post-implementation performance measurement.
• Build data literacy through guidance, documentation, and practical self-service reporting support.

Governance and Compliance

• Follow company data governance, information classification, privacy, and security requirements.
• Maintain clear documentation, version control, validation evidence, and change history for analytical products