Lead Data Scientist – AI & ML Solutions for Scent Business

About the role

The Lead Data Scientist leads the design, development, localization and production deployment of advanced machine learning, generative AI and agentic solutions for IFF's Scent business. Working across R&D, formulation and other business domains, the role translates scientific and business needs into robust models, reusable components and intuitive AI-enabled applications, adapts globally developed internal AI capabilities for the Chinese market and applies state-of-the-art methods to IFF data and use cases. The position is based in Shanghai.

Key responsibilities

• Lead the end-to-end design, development, evaluation and production delivery of machine learning, generative AI and agentic solutions, turning complex problems into reusable capabilities rather than one-off analyses.
• Rapidly replicate, evaluate and apply published methods and models to IFF data and use cases, establishing reproducible pipelines, evaluation harnesses and clear performance criteria.
• Collaborate closely with the AI Chemist Lead on R&D chemistry and molecular discovery, and adapt AI applications in the Creative and Consumer domains to the Chinese market.

Required profile

• PhD or master's degree in data science, computer science, machine learning, statistics, engineering, chemistry, physics, computational biology or another quantitative STEM discipline.
• 5+ years of applied data science or machine learning experience in industry, with models and AI applications delivered from problem definition through production use.
• Proven expertise in machine learning, deep learning, statistical modeling, generative AI, foundation models, retrieval-augmented generation and agentic workflows.
• Solid understanding of scientific data and workflows, Chinese AI models and local technology ecosystems, and the ability to localize AI products for the Chinese market.
• Ability to work independently, turn ambiguous needs into technical specifications and guide junior data scientists.

Required skills

• Production ML engineering, reproducible pipelines, APIs, cloud platforms and MLOps practices.
• Model evaluation, data quality assessment and hands-on model selection, adaptation and fine-tuning.
• Technical leadership and collaboration across data science, engineering, UX, scientific and business teams.

What we offer

• Opportunities to learn and develop across regions, with exposure to global projects and worldwide initiatives.
• Competitive compensation and benefits package, including performance incentives.