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Senior scientist - data science & ai, industrial process analytics

Genf
Firmenich
Inserat online seit: 29 April
Beschreibung

Senior Scientist - Data Science & AI, Industrial Process Analytics Location: Delft(NL) OR Geneva(CH) Are you excited to apply modern data science to real production plants, help process engineers act faster, smarter, and deliver measurable sustainability impact? Join our Industrial Process Analytics team to build advanced analytics that optimize chemical and biochemical manufacturing at scale. Key responsibilities: * Design, build, and ship scalable data science applications for manufacturing - from first idea to validated, deployed product. * Implement model- and data-driven approaches that support plant engineers and operators in day-to-day decisions. * Collaborate in multi-disciplinary teams (data scientists, process/chemical engineers, cloud & data engineers, reliability and production experts) to improve yield, throughput, quality, reliability, and sustainability. * Generate insights and convert them into measurable impact. * Champion a data-driven mindset across sites; communicate results with clarity to technical and non-technical stakeholders. * Contribute to best practices for data analysis, coding and MLOps. * Stay up to date with state-of-the-art methods, scout and implement new technology in-house We offer: * Direct impact on manufacturing operations and sustainability KPIs. * A global Advanced Analytics team focused on optimizing biotech and chemical processes-fully aligned with dsm-firmenich-s manufacturing excellence strategy. * Real-world challenges and exposure to all businesses. Opportunity to contribute strongly to both manufacturing operations as well as S&R up- and downscaling. * An experienced, supportive community that has optimized plants worldwide-and room to grow your expertise in both ML and manufacturing. You Bring: * PhD or similar experience in (Bio)Chemical Engineering or a related field, or Data Science/Statistics/Computer Science. * 3-7 years of additional academic or industrial work experience in manufacturing data sc...

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