At a Glance
- Tasks: Curate and validate scientific data, develop databases, and implement data analysis techniques.
- Company: Join BIOVIA, a leader in scientific data and informatics solutions.
- Benefits: Professional growth, access to training, and a collaborative work culture.
- Other info: Dynamic environment with opportunities for skill development and teamwork.
- Why this job: Make a real impact in science by enhancing data resources for researchers.
- Qualifications: Master's or Ph.D. in a scientific discipline with data analysis experience.
The predicted salary is between 45000 - 60000 £ per year.
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, characterization techniques, and substance or material selection processes.
- Proficiency in data analysis and programming languages such as Python (with libraries like Pandas, NumPy, Scikit‑learn), R, or similar.
- Experience with database management systems (SQL or NoSQL).
- Familiarity with scientific databases and ontologies (e.g., Materials Project, ChEMBL, PubChem, 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.
Scientific Data Engineer in Cambridge employer: Dassault Systemes
At Dassault Systèmes, we pride ourselves on being an excellent employer that fosters a culture of collaboration and innovation. As a Scientific Data Engineer, you will have access to professional growth opportunities and a supportive learning environment, allowing you to advance your career while working alongside talented cross-functional teams in a cutting-edge scientific data platform. Our commitment to employee development and a dynamic work culture makes us an attractive choice for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Scientific Data Engineer in Cambridge
✨Get Involved in Research Communities
Dive headfirst into the scientific research world by joining relevant communities and forums. Engage in discussions, share your insights, and even attend conferences or seminars in your field. This not only boosts your visibility but can also lead to potential job opportunities—don't forget to connect with like-minded folks!
✨Show Off Your Research Projects
Have you worked on any cool research projects? Make it easy for potential employers to see your work by creating a portfolio or a personal website. This way, when you apply for roles like the one at Dassault Systemes, you can point them to your projects and publications, showcasing your expertise directly.
✨Utilise Professional Networks
Networking is key in scientific research. Join professional bodies or organisations related to your field. They often have job boards and resources tailored for job seekers. Make connections with professionals who may know about openings or can give you tips on landing a full-time position.
✨Keep Your Eyes on Openings & Apply Directly
Don’t just rely on job boards! Keep an eye on the careers section of the websites of companies like Dassault Systemes. Apply directly through their website because sometimes they post jobs there before anywhere else. Plus, it shows your proactive approach!
We think you need these skills to ace Scientific Data Engineer in Cambridge
Some tips for your application 🫡
Highlight Your Research Experience:When applying for a full-time role in scientific research, make sure to emphasise your research experience prominently in your CV. Share specific projects you’ve worked on, the methodologies you used, and any significant findings. If you’ve published papers or presented at conferences, definitely include that too – it shows you’re on it in the academic world!
Tailor Your Cover Letter to the Research Area:Your cover letter should reflect your passion for the specific area of research at Dassault Systemes. Mention relevant experiences that align with the organisation’s goals or projects. This shows that you’ve done your homework and are genuinely interested in the position – plus, it helps us see how you’d fit into the team dynamics.
Showcase Your Data Analysis Skills:In scientific research, data analysis skills are a big deal! Make sure to detail any relevant analytical tools or software you’re familiar with, like R, Python, or statistical packages. Employers are keen to know you can handle the data-heavy elements of the role, so add specific examples where you’ve used these skills effectively.
Discuss Your Future Research Goals:In your motivation section, it’s a great idea to talk about your future research goals and how they align with the work being done at Dassault Systemes. This shows that you’re not just looking for any job, but rather a chance to contribute meaningfully to the field. We love to see applicants who are forward-thinking and enthusiastic about their research journey!
How to prepare for a job interview at Dassault Systemes
✨Showcase Your Research Skills
In scientific research, it’s crucial to demonstrate your ability to design and conduct experiments. Come armed with examples of past projects where you've developed hypotheses, collected data, and analysed results. Be ready to discuss any specific methodologies or tools you’ve used, like PCR techniques or statistical software.
✨Prepare for Technical Questions
Expect some technical questions specific to your field. Make sure you're up to speed with recent advancements in scientific research related to the role at Dassault Systemes. Brush up on concepts relevant to their projects and be prepared to discuss how you would approach a specific research problem or challenge they might face.
✨Know Your Publications
If you've authored or co-authored any papers, be prepared to discuss them! Highlighting your contributions to published research can really set you apart. It shows not only your expertise but also your ability to communicate complex ideas clearly, which is key in scientific research roles.
✨Exhibit Your Team Spirit
In full-time roles, collaboration is often at the heart of scientific research. Prepare examples that show how you've successfully worked in teams, dealt with conflicts, or contributed to group projects. We want to know how you can work effectively with the team at Dassault Systemes to drive research projects forward.
