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Location
In office (Gorinchem)

Confirmed on the employer's own hiring board on Nov 10, 2026. First seen by Alion on Nov 10, 2026.

Overview
Company
Impact
Profile match
Corbion is a sustainable ingredients company headquartered in Amsterdam, Netherlands, that uses fermentation and biotechnology to produce lactic acid and its derivatives, food preservation ingredients, biochemicals, biomedical polymers and algae-based ingredients. It serves food markets such as bakery, meat, dairy and beverages, biomedical uses such as drug delivery and medical devices, and agriculture, electronics, pharma, cleaning and personal care, with plants including Gorinchem, Totowa, Lenexa, Blair, Araucaria and Rayong. The company hires production operators and supervisors, fermentation technicians, planning engineers, sales managers and procurement, HR, payroll and IT staff.

At Corbion, we exist to champion preservation in all its forms, preserving food and food production, health, and our planet.

The role

Are you a Data Scientist who wants to use advanced analytics to solve real-world challenges in an international manufacturing environment?

As a Data Scientist, you will join and strengthen our Data Science team and report to a Principal Data Scientist. You will help transform complex manufacturing, laboratory, and business data into actionable insights that improve product quality, process performance, yield, and productivity and overall decision-making.

Your work will range from exploratory data analysis and troubleshooting to predictive and prescriptive modelling. For example, you may investigate why a plant is losing yield, combine high-frequency sensor data with laboratory results, identify the root cause, and develop a model that recommends optimal process parameters or recipe settings.

This is a global role in which you will collaborate with colleagues across manufacturing, innovation, and commercial functions in different countries. You will also play an important role in making advanced analytics understandable and accessible to stakeholders with different levels of technical expertise.

Key Responsibilities

  • Use advanced analytics, statistical methods, machine learning, and AI to generate actionable insights and measurable business impact across manufacturing, innovation, and commercial activities.
  • Analyze large and complex datasets, including high-frequency plant and sensor data, laboratory results, and relevant metadata.
  • Prepare imperfect real-world datasets for analysis through data cleaning, preprocessing, feature engineering, and exploratory data analysis.
  • Develop predictive models to support areas such as product-quality prediction, process monitoring, troubleshooting, and performance improvement.
  • Apply prescriptive analytics to identify optimal process conditions, parameter settings, input variables, or recipe configurations.
  • Deliver statistical consulting in areas such as experimental design, data interpretation, predictive modelling, and advanced statistical analysis.
  • Translate business or scientific questions into clearly defined analytical problems and scalable data-driven solutions.
  • Communicate complex models and analytical findings through clear recommendations, presentations, visualizations, and reports for both technical and non-technical stakeholders.
  • Create data visualizations and reporting solutions using tools such as Power BI.
  • Work with cross-functional and international stakeholders to advance digitalization and data-driven decision-making across multiple manufacturing locations.
  • Explore, develop, and pilot innovative machine-learning and AI solutions while recognizing the importance of data quality, data maturity, and sound statistical foundations.
  • Promote best practices in coding, version control, documentation, model development, and data-science methodologies.
  • Support capability building by delivering training sessions, workshops, and practical guidance to users and stakeholders.
  • Contribute to the continuous development of the organization’s data-science and digital capabilities.

You bring

Requirements

  • A master’s degree in Data Science, Computer Science, Statistics, Engineering, Mathematics, Chemistry, Chemical Engineering, or another relevant STEM discipline. A PhD is welcome. A bachelor’s degree may also be considered when combined with substantial relevant industry experience.
  • At least a few years of relevant experience applying data science in an industrial environment.
  • Experience with manufacturing or process data and an affinity with process manufacturing, chemistry, biochemistry, fermentation, or a related scientific field.
  • Strong proficiency in Python and the ability to independently build, evaluate, explain, and improve analytical and machine-learning models.
  • A solid understanding of the statistical and theoretical principles behind machine learning, including the ability to explain why a particular model or method is appropriate.
  • Demonstrable experience using machine learning or advanced statistical modelling to solve real-world problems and create measurable value.
  • Experience with data preparation, exploratory data analysis, feature engineering, predictive modelling, and model evaluation.
  • The ability to work with complex data from different sources and frequencies, such as sensor data, laboratory data, process data, and contextual metadata.
  • Experience with data visualization and reporting tools such as Power BI.
  • Strong analytical, critical-thinking, and problem-solving skills, combined with a practical focus on turning data into business value.
  • Excellent communication skills, with the ability to translate complex algorithms and technical findings into recommendations that non-technical stakeholders can understand and act upon.
  • The ability to independently manage multiple projects and priorities while maintaining a proactive and results-oriented approach.
  • A collaborative mindset and the ability to work effectively in cross-functional and international teams.

Preferred

  • Experience in a global process-manufacturing environment.
  • Knowledge of manufacturing optimization, product-quality prediction, yield improvement, process troubleshooting, or productivity optimization.
  • Experience with chemometrics, Process Analytical Technology, spectroscopic data, fermentation data, or other scientific and industrial analytics applications.
  • Proficiency in R in addition to Python.
  • Experience with SQL or other tools used to access and gather data.
  • Experience with Microsoft Azure, Azure DevOps, cloud-based analytics platforms, code repositories, and version control.
  • Experience developing scalable analytics solutions and supporting the digitalization of manufacturing processes.
  • Exposure to AI-enabled development tools for code review, optimization, or related data-science activities.

What we offer

  • The opportunity to apply data science to tangible, high-impact challenges in manufacturing, innovation, and commercial operations.
  • A varied role in which you can work across the full analytical cycle, from understanding the business question and preparing complex datasets to developing models and presenting recommendations.
  • Access to challenging industrial datasets, including high-frequency sensor data, laboratory results, and manufacturing-process information.
  • The chance to make a visible contribution to process optimization, product quality, yield improvement, and digital transformation.
  • An international working environment with exposure to stakeholders and manufacturing locations across different regions.
  • The opportunity to help shape and further develop a growing data-science capability within the organization.
  • Collaboration with colleagues whose expertise includes data science, chemometrics, Process Analytical Technology, fermentation, and data management.
  • Room to explore new analytical methods, pilot machine-learning and AI solutions, and help establish effective standards for coding, documentation, and model development.
  • The opportunity to make advanced analytics understandable and useful throughout the organization by sharing your expertise through training, workshops, and stakeholder guidance.
  • Challenging and meaningful work at the intersection of data science, science, innovation, and manufacturing, with a direct contribution to creating sustainable value.

About Corbion

Corbion is a sustainable ingredients company dedicated to preserving what matters, including food and food production, health, and the planet. We specialize in lactic acid, lactic acid derivatives, food preservation solutions, functional blends, and algae ingredients, using our deep application and product knowledge to propel nature’s ingenuity through science. With more than a century of experience, we continue working side-by-side with our customers to make our cutting-edge technologies work for them. Leveraging our advanced capabilities in fermentation and preservation technology, we help customers differentiate their products in diverse markets ranging from food and animal nutrition to home & personal care, pharmaceuticals, electronics, medical devices, and bioplastics.In 2025, Corbion generated annual sales of €1,267.4 million and had a workforce of 2,408 FTE. For more information: www.corbion.com

Corbion is an equal opportunity employer and committed to a diverse workplace. All applicants will be considered equally.

Corbion does not accept unsolicited resumes from individual recruiters or third party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers. All candidates must be submitted by approved Corbion vendors who have been expressly requested to make a submission by our Talent Acquisition team for a specific job opening. No placement fees will be paid to any firm unless such a request has been made by the Corbion Talent Acquisition team and such candidate was submitted to the Corbion Talent Acquisition Team.

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