· Develop and implement core Smart Scheduling tools for short-term resource planning across BU ES plants, to improve planning accuracy and operational efficiency

· Customize planning models and tools for different plant needs to support flexible production, by working closely with plant PPC and IE teams to gather requirements and validate solutions.

· Drive cost modeling initiatives for materials, energy, spare parts, and labor in order to enable cost transparency and identify improvement areas, by leveraging the existing cost database and aligning with controlling and operations.

· Establish cross-plant benchmarking models to highlight performance gaps and best practices, supporting continuous improvement and cost-saving initiatives, through data consolidation and comparative analysis.

· Ensure continuity and risk mitigation in data analytics by acting as a backup and collaborator to the current data analyst, maintaining tool reliability and responsiveness during peak workloads or absences.

· Collaborate with plant PPC an IE teams to align tool development and analytics work with operational strategies and KPIs, ensuring that solutions are practical, scalable

Your Profile

· Advanced Analytics and Predictive Modeling: Deep understanding of data science, predictive analytics with strong proficiency in R language / Python (Preferred Certification: CDA Level 2 is a plus)

· Knowledge of algorithms and data integration to optimize efficiency
Strong analytical and problem-solving skills, capable of identifying and addressing inefficiencies in production systems through data-driven methods

· Supply Chain and Production Management: Broad knowledge of production processes, resource management, and supply chain dynamics. This includes familiarity with dynamic scheduling and optimization to meet production demands and minimize resource waste.

· Cost Analysis and Benchmarking: Strong expertise in cost analysis, operational cost structures

· 5+ years of experience in industrial engineering, operations or production planning in a manufacturing environment

Once a resume is submitted to the recruiting company, it is considered that the applicant agrees to the collection, processing, use, and disclosure of their resume and other personal information by the recruiting company for recruitment purposes.
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