Cheminformatics Scientist

Join us and celebrate the beauty of human experience. Create for happier, healthier lives, with love for nature. Together, with our customers, we deliver food innovations, craft inspired fragrances and develop beauty and wellbeing solutions. There's much to learn and many to learn from, with more than 16,000 employees around the world to explore ideas and ambitions with. In the USA, we develop, market and produce a wide array of solutions from our 25 most innovative sites, based across the country. Stretch your skills, create and get inspiration from passionate colleagues. Every day, your energy, your thirst for knowledge, and your creativity will shape our future, making a positive difference on billions of people. Every essence of you enriches our world. We are Givaudan. Human by nature. Givaudan Flavors Science & Technology is looking for a Cheminformatics Scientist to join a versatile team advancing flavor ingredient discovery. You will apply cheminformatics, machine learning, and AI to develop novel aroma and taste molecules while collaborating across research teams to build data-driven discovery workflows. Your Title Cheminformatics Scientist Your Location Onsite (Givaudan facility) You Will Report To Flavors Science & Technology Computational Sciences Lead Responsibilities Design and implement cheminformatics algorithms and workflows to accelerate flavor ingredient discovery across aroma and taste modalities. Develop, validate, and deploy predictive models using QSAR, machine learning, artificial intelligence, and 2D/3D computational approaches for small-molecule analysis and property prediction. Apply statistical, cheminformatics, and machine learning methods to improve hit identification and hit-to-lead processes. Collaborate with chemistry and research teams to integrate AI/ML and cheminformatics into DMTA workflows. Enhance databases and computational pipelines to support data-driven research. Develop computational tools, visualizations, and analytical programs for molecular data analysis. Communicate scientific insights across teams and support collaboration. Provide mentoring and promote best practices in data integrity, reproducibility, and FAIR data principles. Your Professional Profile Includes PhD or Master's degree in Cheminformatics, Computational Chemistry, Chemistry, or a related discipline. Expertise in structure-based drug design (SBDD), including docking, pharmacophore modeling, virtual screening, and molecular dynamics. 3+ years of experience with ligand-based modeling (QSAR, 2D/3D virtual screening) and protein modeling (e.g., homology modeling, protein-protein docking). Data science and statistical analysis skills, including exploratory data analysis and model validation. Advanced programming skills in Python or R, plus proficiency in an additional language, following coding best practices. Experience with cheminformatics tools (e.g., RDKit, OpenEye) and molecular analysis techniques such as library enumeration, similarity analysis, clustering, and dimensionality reduction. Industry familiarity with SQL/databases, analytics tools (KNIME, Spotfire, Shiny), and NLP/LLMs in scientific contexts; relevant industry experience. Compensation and Benefits The established salary range for this position is $80,000-120,000k, depending on individual qualifications and experience. Employees receive medical, dental, and vision coverage, along with a high-matching 401(k) retirement plan. #LI-Onsite At Givaudan, you contribute to delightful taste and scent experiences that touch people's lives. You work within an inspiring teamwork culture - where you can thrive, collaborate and learn from other talented and passionate people across disciplines, regions and divisions. Every essence of you enriches our world. Diversity of perspectives fuels innovation and fosters deeper connections with our employees, customers, and partners. At Givaudan, we are dedicated to cultivating an inclusive environment where every individual's voice is valued and has the power to shape our world. Join us in making a difference together.