Job
Description
As a member of the team at Barry Callebaut, you will play a crucial role in shaping the future of maintenance and manufacturing performance by leveraging data, automation, and AI technologies. Your responsibilities will include: - Building and deploying tools that utilize machine learning and AI to extract actionable insights from maintenance and production data, enhancing factory productivity. - Delivering insights in clear, business-ready formats such as Power BI reports, dashboards, and presentations. - Supporting and evolving Barry Callebaut's CMMS ecosystem and MRO master-data governance to ensure data accuracy, harmonization, and analytics readiness through automated, reusable pipelines. In your role, you will: - Develop and deploy data pipelines and AI-powered analytics to cleanse, classify, and interpret maintenance and spare-parts data, including text extraction, anomaly detection, and loss pattern recognition. - Integrate OpenAI API and other ML models into workflows to scale insights. - Design, document, and maintain datasets and KPIs used globally in Power BI. - Identify trends, patterns, and anomalies in asset and work-order data to provide actionable reliability insights. - Own end-to-end delivery from data extraction to Power BI deployment and adoption by business stakeholders. - Collaborate cross-functionally with Manufacturing Operations, Process Excellence, Engineering, and Sourcing teams to support cost-reduction and reliability programs. - Act as the global data owner for spare-parts and CMMS master data, driving data cleansing, duplicate elimination, and governance improvements. - Continuously industrialize and document solutions to ensure that dashboards, code, and models remain sustainable and reusable. - Promote the democratization of data through self-service analytics, coaching colleagues to use Power BI datasets and standardized definitions. Qualifications required for this role include: - Masters or bachelor's degree in engineering, IT, or Data & Computer Science. - 5+ years of experience with Python in machine learning and API calls. - Proficiency in data visualization/reporting tools such as PowerBI, SSRS, Tableau, or SAC, specifically DAX and Power M. - Basic understanding of manufacturing automation (PLC, SCADA, MES, Historian, OSI PI). Essential experiences and knowledge expected include: - More than 5 years of experience with Python as a data scientist, with proficiency in data exploration, machine learning, and visualization. - Preferably more than 1 year exposure to industrial data from the processing or manufacturing industry or power plants. - Experience integrating or automating workflows using OpenAI API or similar LLM platforms (preferred). - Demonstrated experience in data analysis, KPI development, and reporting. - Strong understanding of maintenance operations and asset management principles. - Reliability and/or maintenance management background is highly desirable, as well as experience with CMMS (Computerized Maintenance Management System) is highly desirable. - Excellent analytical, problem-solving, and critical thinking skills. - Ability to communicate complex data insights in a clear and understandable manner to both technical and non-technical audiences. - Self-motivated and able to work independently as well as part of a team. If you join the Barry Callebaut team, you will be part of an inclusive environment where diversity is celebrated, and individuals are encouraged to grow and contribute to sustainable growth. As a member of the team at Barry Callebaut, you will play a crucial role in shaping the future of maintenance and manufacturing performance by leveraging data, automation, and AI technologies. Your responsibilities will include: - Building and deploying tools that utilize machine learning and AI to extract actionable insights from maintenance and production data, enhancing factory productivity. - Delivering insights in clear, business-ready formats such as Power BI reports, dashboards, and presentations. - Supporting and evolving Barry Callebaut's CMMS ecosystem and MRO master-data governance to ensure data accuracy, harmonization, and analytics readiness through automated, reusable pipelines. In your role, you will: - Develop and deploy data pipelines and AI-powered analytics to cleanse, classify, and interpret maintenance and spare-parts data, including text extraction, anomaly detection, and loss pattern recognition. - Integrate OpenAI API and other ML models into workflows to scale insights. - Design, document, and maintain datasets and KPIs used globally in Power BI. - Identify trends, patterns, and anomalies in asset and work-order data to provide actionable reliability insights. - Own end-to-end delivery from data extraction to Power BI deployment and adoption by business stakeholders. - Collaborate cross-functionally with Manufacturing Operations, Process Excellence, Engineering, and Sourcing teams to support cost-reduction and
