Data Scientist

Job SummaryResponsible for exploring complex datasets, developing machine learning (ML) and artificial intelligence (AI) models, and delivering actionable insights that drive business value.

As a Data Scientist in the Cognitive & Data Science team, your key responsibilities will be:

- Landscaping: Proactively and autonomously monitor the progress in your field, run competitive analysis and identify gaps and opportunities in knowledge and capabilities.
- Experimentation: Continuously experiment with new techniques, tools, and technologies to stay up to date with the latest advancements in ML/AI and data science.
- Collaboration: Work closely with cross-functional teams, including operations, marketing, and R&D, to understand business needs and develop data-driven solutions that meet those needs.
- Pipeline management: Influence the generation of business-relevant projects; proactively screen project pipeline, manage competing priorities, engage with stakeholders to align on the approach and ensure the field of expertise is leveraged to create business value.
- Data Exploration: Analyze large and complex datasets to identify patterns, trends, and correlations that can inform business decisions.
- Model Development: Design, develop, and deploy ML/AI models using popular frameworks to solve specific business problems, such as molecular prediction, demand forecasting, or process optimization.
- Knowledge Sharing: Harvest, funnel, document and disseminate knowledge, findings, methods, and best practices from both internal and external sources; Document and present to the team and organization, ensuring knowledge sharing and collaboration.
- Communication: Present in an impactful way the approach and/or insights at various stages to stakeholders - project team, customers, leadership. Be the ambassador of internal and external recognition of IFF expertise in data science.

Required data science technical skills:
Proficiency in one or more programming languages (Python, R or MATLAB):

- Ability to write efficient, well-organized code.
- Understanding of object-oriented programming principles (OOP) and functional programming concepts.

Hands-on experience with popular ML/AI frameworks (TensorFlow, PyTorch, Scikit-learn, or Keras):

- Familiarity with deep learning techniques.
- Experience building and deploying machine learning models using various frameworks.

Strong understanding of statistical modeling and data analysis principles:

- Knowledge of hypothesis testing, confidence intervals, and regression analysis.
- Familiarity with Bayesian inference and frequentist statistics.

Experience working with large datasets and databases:

- Familiarity with data warehousing and business intelligence tools.
- Understanding of data governance and compliance regulations.

Experience with data visualization tools (Tableau, Power BI, or Looker). Understanding of cloud computing platforms (AWS, Azure, Google Cloud).

Domain-specific requirements for flavor chemistry:
Familiarity with chemical reaction kinetics and thermodynamics:

- Understanding of chemical equilibrium principles and rate equations.
- Knowledge of common reaction mechanisms.

Knowledge of flavor chemistry principles and concepts:
Experience working with flavor databases and datasets:

- Familiarity with flavor profiling techniques (e.g., descriptive analysis).
- Knowledge of common flavor compounds and their chemical properties is a plus.

Understanding of sensory science principles and methods:

- Familiarity with human perception of taste, smell, and texture.
- Knowledge of sensory testing methods.

Required competencies:

- Drive for results with strong customer focus,
- Dealing with ambiguity, problem solving and creativity,
- Good work/project management skills with timely decision making,
- Interpersonal savvy, ability to thrive in a multicultural environment with high diversity,
- Fluency in English with excellent written and verbal communication skills; additional languages preferred,
- Ability to effectively communicate complex technical concepts to both technical and non-technical stakeholders,

Required experience:

- A strong foundation in mathematical and statistical modeling techniques, ideally in a field related to chemistry: Master's or Ph.D. in Data Science, Computer Science, Statistics.
- 10+ years of experience in data science, ML/AI, computational chemistry or a related field:

- Practical experience working with complex datasets, such as those found in the chemical industry.
- Understanding of data preprocessing techniques, feature engineering, and model evaluation methods.

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