Asks for

The ad says“Design, develop, validate, and deploy explainable predictive ML/AI models to generate actionable insights and business value.”
The ad says“Proven track record developing explainable predictive models, including feature engineering, model selection, validation, interpretability (e.g., regularized elastic net, tree-based models, SHAP), and advanced statistical techniques such as hypothesis testing, Bayesian inference, and uncertainty quantification.”
The ad says“Design and optimize Design of Experiments (DOE), including mixture, factorial, optimal, and space-filling designs, to systematically explore relationships and maximize information from limited resources.”
The ad says“Practical experience developing ML/AI models using TensorFlow, PyTorch, Scikit-learn, or Keras, with familiarity in MLOps principles, tracking, versioning, registries, CI/CD for ML, containerization (Docker), and model monitoring.”
The ad says“Design, develop, and deploy ML/AI models using leading frameworks to address opportunities such as optimization, prediction, and forecasting, while ensuring reproducibility, peer review, and collaborative development through version-controlled code (Git).”
The ad says“Proven track record developing explainable predictive models, including feature engineering, model selection, validation, interpretability (e.g., regularized elastic net, tree-based models, SHAP), and advanced statistical techniques such as hypothesis testing, Bayesian inference, and uncertainty quantification.”
The ad says“Practical experience developing ML/AI models using TensorFlow, PyTorch, Scikit-learn, or Keras, with familiarity in MLOps principles, tracking, versioning, registries, CI/CD for ML, containerization (Docker), and model monitoring.”
The ad says“Design, develop, validate, and deploy explainable predictive ML/AI models to generate actionable insights and business value.”
The ad says“Master’s or Ph.D. in Mathematics, Data Science, Computer Science, Statistics, or a related field, with strong foundations in mathematical and statistical modeling, machine learning algorithms, and their applications.”
The ad says“Proficiency in Python, R, or MATLAB, with understanding of object-oriented and functional programming concepts; familiarity with AWS, Azure, or Google Cloud platforms.”
The ad says“Practical experience developing ML/AI models using TensorFlow, PyTorch, Scikit-learn, or Keras, with familiarity in MLOps principles, tracking, versioning, registries, CI/CD for ML, containerization (Docker), and model monitoring.”
The ad says“Proficiency in Python, R, or MATLAB, with understanding of object-oriented and functional programming concepts; familiarity with AWS, Azure, or Google Cloud platforms.”
The ad says“Practical experience developing ML/AI models using TensorFlow, PyTorch, Scikit-learn, or Keras, with familiarity in MLOps principles, tracking, versioning, registries, CI/CD for ML, containerization (Docker), and model monitoring.”
The ad says“Proficiency in Python, R, or MATLAB, with understanding of object-oriented and functional programming concepts; familiarity with AWS, Azure, or Google Cloud platforms.”
The ad says“Practical experience developing ML/AI models using TensorFlow, PyTorch, Scikit-learn, or Keras, with familiarity in MLOps principles, tracking, versioning, registries, CI/CD for ML, containerization (Docker), and model monitoring.”
The ad says“Master’s or Ph.D. in Mathematics, Data Science, Computer Science, Statistics, or a related field, with strong foundations in mathematical and statistical modeling, machine learning algorithms, and their applications.”
The ad says“Practical experience developing ML/AI models using TensorFlow, PyTorch, Scikit-learn, or Keras, with familiarity in MLOps principles, tracking, versioning, registries, CI/CD for ML, containerization (Docker), and model monitoring.”
The ad says“Proven track record developing explainable predictive models, including feature engineering, model selection, validation, interpretability (e.g., regularized elastic net, tree-based models, SHAP), and advanced statistical techniques such as hypothesis testing, Bayesian inference, and uncertainty quantification.”

Values

The ad says“Work with structured and experimental datasets while ensuring data integrity, governance, and compliance, and leverage cloud platforms such as AWS, Azure, and Google Cloud for scalable data solutions.”
The ad says“Work with structured and experimental datasets while ensuring data integrity, governance, and compliance, and leverage cloud platforms such as AWS, Azure, and Google Cloud for scalable data solutions.”
The ad says“Master’s or Ph.D. in Mathematics, Data Science, Computer Science, Statistics, or a related field, with strong foundations in mathematical and statistical modeling, machine learning algorithms, and their applications.”
The ad says“Document and present findings, best practices, and methodologies to foster collaboration and continuous learning, maintaining living documentation in Confluence or equivalent platforms.”
The ad says“Work with structured and experimental datasets while ensuring data integrity, governance, and compliance, and leverage cloud platforms such as AWS, Azure, and Google Cloud for scalable data solutions.”
The ad says“Proficiency in modern collaborative development practices; strong understanding of data governance, model governance, compliance regulations, and data visualization tools such as Tableau, Power BI, or Looker.”
The ad says“Master’s or Ph.D. in Mathematics, Data Science, Computer Science, Statistics, or a related field, with strong foundations in mathematical and statistical modeling, machine learning algorithms, and their applications.”
The ad says“Proficiency in modern collaborative development practices; strong understanding of data governance, model governance, compliance regulations, and data visualization tools such as Tableau, Power BI, or Looker.”
The ad says“Master’s or Ph.D. in Mathematics, Data Science, Computer Science, Statistics, or a related field, with strong foundations in mathematical and statistical modeling, machine learning algorithms, and their applications.”
The ad says“Proficiency in modern collaborative development practices; strong understanding of data governance, model governance, compliance regulations, and data visualization tools such as Tableau, Power BI, or Looker.”

Job Summary

Are you passionate about data science? Do you have an interest in chemistry? Are you curious to decode product design, perceptions, and behaviours? The Cognitive & Data Science team is looking for you!

IFF is a global leader in flavors, fragrances, and health & biosciences. We deliver sustainable innovations that elevate everyday products.

This opportunity sits within our Taste business unit where we craft unique, technology-enabled flavor designs that define the identity of food and beverage brands, shape trends in flavor building and fuel market success.

As a key member of our team, you will be responsible for designing efficient experiments (Design of Experiments/DOE), exploring complex high-dimensional datasets, developing and validating predictive machine learning (ML) and artificial intelligence (AI) models, and delivering actionable insights that drive business value. In this role, you will collaborate closely with cross-functional experts in various fields related to flavor creation to bridge data-driven insights with practical outcomes.

Your expertise will help us unlock new opportunities, improve processes, and inform strategic decisions across the organization. Your KPIs will primarily be the internal adoption of the tools as well as the positive impact on win rate and project execution.

Where You will make a difference

To be successful in this role you are a highly skilled Data Scientist with at least 8 years of experience in the field of data science with strong business acumen and passion to apply data-driven methods to real-world data. You know the scientific fundamentals and are agile with the methods, whilst being pragmatic and result oriented. You strongly believe that insights generated through data science can have a direct impact on product design. You thrive in multidisciplinary settings and enjoy tackling open-ended research questions and translating complex analytical findings into clear and meaningful narratives for non-technical stakeholders.

Design and optimize Design of Experiments (DOE), including mixture, factorial, optimal, and space-filling designs, to systematically explore relationships and maximize information from limited resources.
Design, develop, validate, and deploy explainable predictive ML/AI models to generate actionable insights and business value.
Monitor emerging trends in data science and ML/AI, conduct competitive assessments, and evaluate new techniques, tools, and technologies to drive continuous improvement and innovation.
Partner with Operations, Creative, and R&D teams to understand business needs and deliver impactful, data-driven solutions.
Analyze large and complex datasets to uncover patterns, trends, and insights that support business strategy and priorities.
Design, develop, and deploy ML/AI models using leading frameworks to address opportunities such as optimization, prediction, and forecasting, while ensuring reproducibility, peer review, and collaborative development through version-controlled code (Git).
Document and present findings, best practices, and methodologies to foster collaboration and continuous learning, maintaining living documentation in Confluence or equivalent platforms.
Work with structured and experimental datasets while ensuring data integrity, governance, and compliance, and leverage cloud platforms such as AWS, Azure, and Google Cloud for scalable data solutions.
Apply domain expertise in flavor chemistry, sensory science, and human science, incorporating first-principles modeling and experimental design to advance data-driven approaches and innovation.

What Makes You the Right Fit

Master’s or Ph.D. in Mathematics, Data Science, Computer Science, Statistics, or a related field, with strong foundations in mathematical and statistical modeling, machine learning algorithms, and their applications.
Minimum 8 years of experience in data science, ML/AI, statistical modeling, or related areas.
Demonstrated hands-on expertise in Design of Experiments (DOE), including mixture, factorial, response-surface, and optimal designs.
Proven track record developing explainable predictive models, including feature engineering, model selection, validation, interpretability (e.g., regularized elastic net, tree-based models, SHAP), and advanced statistical techniques such as hypothesis testing, Bayesian inference, and uncertainty quantification.
Hands-on experience with complex datasets in the chemical, manufacturing, sensory, or consumer research fields, including data preprocessing, feature engineering, and model evaluation.
Practical experience developing ML/AI models using TensorFlow, PyTorch, Scikit-learn, or Keras, with familiarity in MLOps principles, tracking, versioning, registries, CI/CD for ML, containerization (Docker), and model monitoring.
Proficiency in Python, R, or MATLAB, with understanding of object-oriented and functional programming concepts; familiarity with AWS, Azure, or Google Cloud platforms.
Proficiency in modern collaborative development practices; strong understanding of data governance, model governance, compliance regulations, and data visualization tools such as Tableau, Power BI, or Looker.
Excellent communication and collaboration skills, with the ability to translate complex technical concepts for technical and non-technical stakeholders, manage projects effectively, work in multicultural environments, and demonstrate customer focus, problem-solving, creativity, adaptability, and a commitment to continuous learning and innovation.

Why Choose Us?

8% holiday allowance and a performance based annual bonus scheme (AIP)
Individual Choice Budget (IKB), which can be used flexibly (e.g., additional vacation days or monthly payout)
25 vacation days plus additional ADV days
Commuting allowance (€0.23/km, up to 72 km one way) or full reimbursement of public transport (2nd class)
Attractive pension scheme, company-paid disability insurance and enhanced parental leave
Access to an Employee Assistance Program (EAP) providing discreet wellbeing, financial, and personal support, along with employee resource groups and year-round activities such as workshops, sports events, volunteering, and social gatherings.

We are a global leader in taste, scent, and nutrition, offering our customers a broader range of natural solutions and accelerating our growth strategy. At IFF, we believe that your uniqueness unleashes our potential. We value the diverse mosaic of the ethnicity, national origin, race, age, sex, or veteran status. We strive for an inclusive workplace that allows each of our colleagues to bring their authentic self to work regardless of their religion, gender identity & expression, sexual orientation, or disability.

Visit IFF.com/careers/workplace-diversity-and-inclusion to learn more