Data Science Lead
Vor 3 Stunden
Lindau, Zurich, Schweiz
Givaudan
Vollzeit
Kostenlos per E-Mail oder Google
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ppJoin us and celebrate the beauty of human experience. Create for happier, healthier lives, with love for nature. Together, with kindness and humility, we deliver food innovations, craft inspired fragrances and develop beauty and wellbeing solutions that make people look and feel good. There’s much to learn and many to learn from, with more than 17,000 employees around the world to explore ideas and ambitions with. Dive into varied, flexible, and stimulating environments. Meet empowered professionals to partner with, befriend, and stretch your skills alongside. Every day, your energy, your creativity, and your determination 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. /ppThis role oversees the development and delivery of AI and data science solutions for scientific and chemistry-related applications, including research, laboratory, and industrial RD environments. Acting as a bridge between Data Science and ST teams, the role ensures robust scientific interpretation, high-quality data governance, and the integration of machine learning and advanced modeling into research and operational workflows. In this role you will report to the Data Science Manager. /ph3Your purpose /h3ulliLead Data Science AI initiatives in Science and Technology (ST) scope, by combining advanced data science leadership with deep scientific domain understanding /liliProvide guidance and support to Data Scientists and AI Engineer in the design and development of complex data models, algorithms, and scientific data analysis approaches that enhance decision-making and business outcomes /liliIn charge of the planning and iterative delivery of Data Science AI solutions to deliver robust and actionable products for Science and Technology /liliContribute to the definition and improvement of Data Science AI methodologies, including scientific modeling and experimental data interpretation frameworks. /li /ulh3Your Core Responsibilities /h3h3Project Management /h3ulliLead the execution and delivery of data science projects, including scientific and chemistry-related initiatives (e.g., research and discovery, analytical chemistry, innovation knowledge management, …) /liliEnsure delivery meets quality, regulatory, and methodology standards, including traceability and reproducibility of scientific results /li /ulh3Model Development /h3ulliGuide the design and implementation of advanced statistical models, machine learning algorithms, and data mining techniques to scientific and chemistry related initiatives including chemical processes and formulations as well as experimental and laboratory data. /liliIntegrate domain knowledge (chemistry or related fields) into Data Science and AI modeling approaches /liliExplore and apply knowledge of existing and emerging data science principles, theories, and techniques on model development and evaluation /li /ulh3Scientific Data Analysis Interpretation /h3ulliOversee the analysis of experimental, laboratory and process data (e.g., spectroscopy, chromatography, reaction data) /liliEnsure sound scientific interpretation of model outputs, aligned with chemical principles and industrial constraints /liliSupport teams in translating scientific hypotheses into testable data science solutions /li /ulh3Performance Monitoring /h3ulliMonitors and evaluates the performance of data science initiatives, using metrics and KPIs to assess impact and identify areas for improvement /li /ulh3Data GovernanceulliIn compliance with global enterprise data governance standards, contributes to the implementation of data governance practices, ensuring data quality, integrity, and compliance across science and technology datasets /liliEnsures adherence to regulatory and industry standards (e.g., traceability, auditability, GxP when applicable) /li /ulh3Cross-Functional Collaboration /h3ulliWorks closely with ST scientists and business stakeholders to identify AI and data science needs, integrate AI and Data science into RD and industrial workflows, enable data-driven scientific decision-making solutions, and support data-driven decision-making /liliActs as a bridge between Data Science and Science Technology experts /li /ulh3Your Profile /h3h3Academic Background /h3ulliPhD or master's degree in chemistry, Data Science, Computer Science, Statistics, Mathematics, or a related field /li /ulh3Professional Experience /h3ulli5+ years of experience in data science or analytics /liliExperience in scientific, laboratory, or industrial RD environments /lili3+ years in a leadership or managerial role /liliStrong interdisciplinary background combining data science and scientific expertise is highly preferred. /liliFluency in French and/or German is an advantage. /li /ulh3Technical Skills /h3ulliDomain knowledge: Chemistry, Chemical Engineering, Pharmaceutical or related scientific discipline /liliTechnical Expertise: Proficiency in data s