Data Quality Clerk

3 weeks ago


Didcot Oxfordshire, United Kingdom Scot Lewis Associates Full time €40,000

Data Steward - Didcot - £40000
We are seeking a motivated and detail-oriented Data Steward to join a dynamic data interoperability team within a cutting-edge genetics research network. This role offers a unique opportunity to develop expertise in data interoperability and data modelling, focusing on integrating diverse datasets at scale. The successful candidate will play a crucial role in linking pre-clinical research models with clinically relevant data to accelerate scientific discoveries and improve patient outcomes.

Identify and escalate data issues to project stakeholders, ensuring data quality and integrity based on established validation metrics.
Collaborate with various stakeholders to survey metadata and data model requirements for a wide range of scientific data modalities.
Contribute to developing and implementing new standards for annotating scientific datasets.
Build and maintain a technical pipeline for mapping relational databases to the Resource Description Framework (RDF) and linking data to create AI-ready knowledge graphs.
Develop and enhance technical skills in Python, SQL, RDF, R, and database management, among other areas as required.
Produce high-quality documentation for collaborative open-source projects and maintain resources using version control systems like Git.
Communicate effectively with stakeholders and the wider scientific community through various platforms, including email, video conferencing, and meetings.
Ensure that all data-capture software and data-linking pipelines comply with FAIR principles.
Work systematically to harmonize metadata across various data types and consult with experts within the network.
Provide comprehensive support for data uploads, corrections, and troubleshooting, as needed for developmental projects.
A strong life sciences or computational degree, or equivalent relevant work experience.
Proven experience in building and managing technical pipelines for data curation and management.
SQL, database management, RDF, SPARQL, or similar.
Experience and knowledge working with complex datasets, including big data for transcriptomics, time-series data, and genomics.
Familiarity with linked data and controlled vocabularies.
Ability to develop and maintain professional working relationships and adapt to evolving project needs.


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