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Scientific Data Engineer

Job in Cambridge, Cambridgeshire, CB21, England, UK
Listing for: Biovia
Full Time position
Listed on 2026-10-14
Job specializations:
  • IT/Tech
    Data Scientist, Data Engineering, Data Analyst
Job Description & How to Apply Below
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

Qualifications:

Master's or Ph.D. in Materials Science, Chemistry, Physics, Biology, Chemical Engineering, or a related scientific discipline with a strong emphasis on data analysis.

Proven experience in scientific data curation, validation, and analysis.

Strong understanding of domain-relevant properties, characterisation techniques, and substance or material selection processes.

Proficiency in data analysis and programming languages such as Python (with libraries like Pandas, Num Py, Scikit-learn), R, or similar.

Experience with database management systems (SQL or No

SQL).Familiarity with scientific databases and ontologies (e.g., Materials Project, ChEMBL, Pub Chem, or ontologies developed by NIST or analogous bodies).

Experience with CAD software, multi-physical simulation tools, or LIMS is a plus.

Excellent communication, collaboration, and problem-solving skills.

Ability to work independently and as part of a global team.

What’s in it for you?

Professional Growth:
Opportunity to advance within the organization

Learning Environment:
Access to training, workshops, and skill development

Collaboration:

Work closely with cross-functional teams

Company Culture:
Work in a culture of collaboration and innovation
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