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Digital Product Owner

GEA Group

Galliera Veneta - Viale Europa permanent

Posted: February 23, 2026

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Quick Summary

Supporting the development of digital and IoT projects, analyzing and improving product reliability and quality through data-driven insights.

Job Description

Responsibilities / Tasks

We are looking for a highly motivated Technical Data Scientist to support operational and quality‑related projects within the digital and IoT domain.
In this role, you will work with raw data from tools, sensors, and industrial production systems to identify patterns, diagnose issues, monitor performance, and improve equipment reliability and product quality.
Your focus will be on delivering actionable insights through rigorous analysis, root‑cause investigation, and real‑time performance monitoring, directly supporting engineering, process, and operations teams.

Key Responsibilities

• Analyze operational and sensor data to identify patterns and meaningful insights.
• Detect recurring issues, performance changes, and sources of variability in production environments.
• Track KPIs and identify anomalies or unexpected behavior.
• Manage end‑to‑end data workflows, from preparation to deployment.
• Use Python to prepare data, build analytical models, and evaluate trends or anomalies.
• Write SQL queries to extract and combine data from internal systems.
• Create dashboards and visual reports highlighting performance and process stability.
• Summarize technical findings clearly to support quick and informed decision‑making.
• Share insights with engineering teams to support troubleshooting and improvement efforts.
• Collaborate with cross‑functional teams to maintain aligned data processes and shared understanding.

Your Profile / Qualifications

What sets you up for success

• Master’s degree in a quantitative or technical field (e.g., Computer Science, Engineering, Mathematics, Physics).
• Strong Python programming skills and experience with data analysis and visualization tools.
• Solid foundation in statistics and time‑series analysis (variability, trends, correlations).
• Familiarity with machine learning concepts and hands‑on experience with modern ML frameworks.
• Good knowledge of SQL and experience with relational databases.
• Experience building backend services or APIs using modern web frameworks.
• Basic understanding of frontend technologies and ability to contribute to simple dashboards or interactive reporting tools.
• Experience with containerized applications (e.g., Docker).
• Comfort with version control tools such as Git.
• Fluent written and spoken English.
• Strong customer orientation and communication skills.
• Autonomy, curiosity, and a strong problem‑solving mindset.
• Ability to work effectively in cross‑functional teams.
• Availability for international travel.

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