Full-Stack Data Scientist (Manufacturing)

Quick Facts

• End-to-end role: raw process data to models to working shop-floor solutions
• Cross-functional collaboration across IT, OT, and plant operations
• Impact areas: energy efficiency, product quality, line capacity, planning, sustainability

Description

Build and deploy AI-driven decision support that helps real-time operations on the shop floor. As a Full-Stack Data Scientist in manufacturing, you translate factory strategy into actionable insights using advanced analytics and machine learning, delivering practical solutions end-to-end—from data and models to production systems.

Responsibilities

• Translate strategy and operational goals into analytics and machine learning solutions to boost plant productivity
• Collaborate with a cross-functional team alongside automation engineers, food technologists, and plant operators
• Design and implement AI advisory systems for operational decisions (via Grafana/Power BI visualization or interfaces with control systems)
• Develop data-based solutions for complex baking and food production challenges
• Co-create solutions with equipment suppliers, startups, and academic partners
• Engage with plant managers, operators, analysts, and IT specialists to align business needs, implementation, and solution architecture
• Coordinate international digital projects by managing deliverables, milestones, risks, and resourcing

Requirements

• Master’s degree in a relevant field (industrial automation, computer science, applied statistics, mathematics, engineering, or machine learning)
• Fluent English and Czech
• 3+ years of advanced analytics experience in a manufacturing context
• Strong coding skills in Python and SQL; solid software design principles and ability to write clean, efficient code
• Cloud experience (preferably Azure) and familiarity with Databricks
• Experience applying state-of-the-art analytics, machine learning, and optimization in manufacturing
• Data engineering experience for manufacturing data and dataset preparation for predictive modeling (data cleaning, feature engineering, data enrichment)
• Experience deploying ML models into production and working with MLOps practices
• Visualization experience for operators and management (Grafana, Power BI)
• Willingness to travel mainly within Europe

Benefits

• Attractive financial package with company car and annual bonus
• Training and certification opportunities within a growing Data & Analytics organization building a modern data platform
• Visible impact on international production performance (energy, quality, line capacity, planning, sustainability)
• Chance to shape the digital transformation of a complex food manufacturing domain
• Supportive work environment with sports and team events
• Development support via LLBG Academy; emphasis on sustainability