Data Scientist, Industrial Analytics

We are looking for an experienced Data Scientist to join our team and support our digitalization initiative. In this role, you will leverage advanced analytics and data science methodologies to optimize manufacturing performance, enable proactive decision-making, and drive measurable operational improvements across the global operations landscape. You will also embed analytics deeply into operational practices to enhance efficiency, reduce costs, and improve overall manufacturing effectiveness.

You will be mainly accountable for:

1. Data-Driven Optimization: Utilizing AI/ML and statistical modeling to analyze manufacturing data, enhance efficiency, reduce costs, and improve throughput.
2. Predictive & Continuous Improvement: Developing predictive models for equipment failures and bottlenecks, supporting Lean/Six Sigma initiatives, and providing insights for Kaizen and value stream mapping.
3. Analytics & Visualization: Conduct root cause analysis, designing KPIs and dashboards, and communicating findings through compelling visualizations to drive informed decision-making.
4. Collaboration & Knowledge Sharing: Working closely with cross-functional teams, documenting best practices, providing training, and ensuring analytics solutions are practical and actionable.

Qualifications for the role

1. 7+ years of experience in applied data analytics or data science, ideally within manufacturing, supply chain, or industrial operations.
2. Hands-on experience with advanced analytics platforms and tools (Python, R, SQL, Time-Series Databases, Power BI, SSRS, Azure ML, Snowflake and more).
3. Proven ability to develop, validate, and deploy predictive and prescriptive models in a real-world setting.
4. Degree in Data Science, Statistics, Industrial Engineering, Computer Science, or a related field.
5. Knowledge of Lean, Six Sigma, or continuous improvement practices is a bonus.
6. Strong communication and visualization skills—able to engage both technical and non-technical stakeholders.
7. Experience working in global, cross-functional teams in complex organizations.
8. Fluent English language skills.