Scientific Data Engineer

The BIOVIA brand of Dassault Systèmes is seeking a highly motivated and skilled Scientific Data Specialist to join our team in expanding our cutting-edge scientific data and informatics platform. This platform empowers scientists and engineers to efficiently discover and select materials, substances, and formulations based on domain knowledge, directly integrating with CAD design, multi-physical simulations, and laboratory experiments. As a Scientific Data Engineer, you will play a crucial role in curating, validating, and ensuring the quality of our scientific database, making it a valuable resource for our users. Role Description & Responsibilities: Data Curation and Validation : Gather, clean, and validate scientific data from diverse sources, including peer-reviewed literature, domain databases, vendor catalogs, and experimental data. Implement rigorous quality control measures to ensure data accuracy, consistency, and completeness. Focus on Material domains and future expansion to other scientific domains Database Development and Maintenance : Contribute to the design and maintenance of our scientific ontology, ensuring efficient data storage, retrieval, domain coverage, and integration with our software platform Pipeline Development : Implement ETL pipelines for ingesting, cleaning, and transforming scientific datasets from multiple sources Data Analysis and Modeling: Apply statistical and machine learning techniques to analyse scientific data, identify trends, and develop predictive models for domain-relevant properties and behaviours Ontology Development and Classification: Develop and maintain a comprehensive scientific ontology and classification system to enable efficient searching and filtering based on substance class, properties, and applications Integration with Software Tools: Collaborate with software engineers to ensure seamless integration of the scientific database with CAD design software, multi-physical simulation tools, and laboratory information management systems (LIMS) User Feedback and Validation: Gather feedback from users (scientists and engineers) to understand their needs and validate the usefulness and accuracy of the scientific data. Conduct user studies and analyse usage patterns to identify areas for improvement Staying Current: Stay up-to-date with the latest advancements in relevant scientific domains, data science, and informatics to continuously improve our platform and data resources Documentation: Maintain comprehensive documentation of data sources, validation procedures, and data models Communication: Collaborate with global business and technical teams to understand data requirements and deliver reliable, high-quality data solutions that support downstream applications and analytics