JOB PROFILE

Build and deploy tools that identify actionable insights from maintenance and production data using machine learning and LLM-based AI to enhance factory productivity. Deliver insights in clear, business-ready formats (Power BI reports, dashboards, presentations). Support and evolve Barry Callebaut’s CMMS ecosystem and MRO master-data governance, ensuring data accuracy, harmonization, and analytics readiness through automated, reusable pipelines.

MAIN RESPONSIBILITIES & SCOPE

Develop and deploy data pipelines and AI-powered analytics to cleanse, classify, and interpret maintenance and spare-parts data (e.g., text extraction, anomaly detection, 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 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

 

EDUCATION, LANGUAGE, SKILLS & QUALIFICATIONS

Master’s or bachelor’s degree in engineering, IT or Data & Computer Science 8+ years of Experience with python in machine learning and API calls Data visualization / reporting tools (PowerBI / SSRS / Tableau / SAC), specifically DAX and Power M Basic understanding of manufacturing automation (PLC / SCADA / MES / Historian / OSI PI)

ESSENTIAL EXPERIENCE & KNOWLEDGE / TECHNICAL OR FUNCTIONAL COMPETENCIES

>8 years’ experience with python as a data scientist, with proficiency in data exploration, machine learning, and visualization Preferably > 1 year exposure to industrial data from 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.

LEADERSHIP COMPETENCIES & PERSONAL STYLE

Proactive: Asks clarification and anticipates problems during design through stakeholder alignment, deep listening skills Ownership mindset: Takes responsibility for data quality, delivery, and adoption. Team player: Clearly communicates with team members and stakeholders’ new functionalities Quality oriented: Delivered results must be reliable and correct and fulfill the purpose with focus on User Experience Attention for details: Ensures data presented to end users is correct and calculations have been validated Strategic thinker: Remains oriented towards to end goal and able to prioritize

At Barry Callebaut, we are committed to Diversity & Inclusion. United by our strong values, we thrive on the diversity of who we are, where we come from, what we’ve experienced and how we think. We are committed to nurturing an inclusive environment where people can truly be themselves, grow to their full potential and feel they belong. #oneBC - Diverse People, Sustainable Growth.