AI & Data Scientist
Indexed description
IFF is a global leader in flavors, fragrances, food ingredients and health & biosciences. We deliver sustainable innovations that elevate everyday products.
Health & Biosciences: Channeling our passion for nature and bioscience into sustainable, life-enhancing technologies that power innovative solutions across healthcare, food, consumer and industrial markets.
The role is based in Wilmington, Delaware, United States (on-site role). Be part of a collaborative, innovative and solution-oriented team where together we can achieve greatness and make a real impact. Your potential is our inspiration.
Where You’ll Make a Difference
- Structure, harmonize and manage data across Global Technical Quality systems, including Laboratory Information Management Systems (LIMS), SAP, SharePoint and other digital platforms.
- Develop and implement data science, machine learning and artificial intelligence solutions that enhance quality processes and scientific decision-making.
- Build and maintain scalable data pipelines supporting structured and unstructured laboratory, manufacturing and technical datasets.
- Design and deploy AI-enabled tools, intelligent agents and automated workflows that improve productivity and streamline technical operations.
- Perform statistical analyses to identify trends, deviations and opportunities for continuous improvement across quality systems.
- Partner closely with Research & Development, Manufacturing, Regulatory Affairs and Global Quality Assurance teams to advance data-driven quality best practices.
- Contribute to the continuous improvement of digital infrastructure, data architecture and Global Technical Quality workflows.
- Ensure data integrity, regulatory compliance and alignment with quality standards and expectations.
- Communicate technical findings, recommendations and business insights clearly to cross-functional stakeholders.
- Bachelor’s degree in Data Science, Computer Science, Data Engineering, Bioinformatics, Biochemistry, Biotechnology, Engineering or a related field.
- At least five years of experience in data science, analytics, data engineering or digital transformation roles.
- Strong expertise in data architecture, data modeling and modern data science methodologies.
- Advanced proficiency in Python, SQL and data integration, transformation and automation tools.
- Experience designing, developing and maintaining enterprise data pipelines for structured and unstructured data sources.
- Hands-on experience with artificial intelligence, machine learning, generative AI and intelligent agent development.
- Strong statistical analysis, data visualization and problem-solving capabilities.
- Experience with enterprise platforms such as LIMS, SAP, SharePoint and Microsoft 365 tools.
- Demonstrated ability to learn new business domains quickly, understand how data is stored and used, and identify opportunities to increase productivity through data-driven solutions.
- Master’s or Ph.D degree in Data Science, Artificial Intelligence, Applied Analytics, Data Engineering or a related discipline.
- Experience working with biotechnology, biochemistry, scientific research or laboratory environments.
- Proven track record developing AI-enabled solutions such as Microsoft Copilot experiences, knowledge bases, agentic workflows and automation platforms.
- Opportunity to work on innovative AI and data science initiatives that directly impact global quality operations.
- Exposure to diverse scientific, laboratory and manufacturing datasets across a global organization.
- Collaboration with experts across Research & Development, Quality, Manufacturing and Digital Technology teams worldwide.
- Continuous learning and professional development opportunities in emerging technologies, artificial intelligence and data science.
- Inclusive workplace that values diverse perspectives, curiosity and innovation.
- Ability to help shape the future of AI-enabled quality excellence across Health & Biosciences.
Visit IFF.com/careers/workplace-diversity-and-inclusion to learn more
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