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6 days ago
We are seeking a detail-oriented data quality analyst to join our team. This role requires expertise in AI-assisted curation, API scrapping, data modeling and schema creation & manipulation.
A strong understanding of multi-omics data types, like transcriptomics, proteomics and single-cell omics technologies is essential for this role. Familiarity with programming languages like Python and clinical data standards such as OMOP, FHIR, and HL7 is a must.
About the Role:This role involves identifying, curating and annotating biological datasets from various omics/clinical modalities, including transcriptomics, proteomics, H&E, clinical trials and single-cell data using APIs and AI tools.
- Automate curation of large interaction datasets to decrease curator workload.
- Build fit-for-purpose conceptual & logical data models.
- Have working knowledge of data models, use-case specific schema and standardize biological data using established ontologies and guidelines.
Ensure high-quality curation and consistency across multiple sources to deliver reliable results.
- Work with cross-functional teams to gather requirements and ensure alignment on biological data curation standards.
- Provide clear and timely updates to stakeholders on the progress of data curation tasks, ensuring transparency and alignment with project goals.
- A degree in Life Sciences, Bioinformatics, or a related field (Master's preferred), with familiarity in bioinformatics tools and databases for data curation.
- Experience with programming languages like Python is a must.
- Skills: Git, basics of prompt engineering, API scrapping & LLM for scientific curation.
- Acquaintance with healthcare/clinical data exchange standards (OMOP, FHIR, HL7).
- Excellent interpersonal and communication skills, both written and verbal.
- 1 year of curation experience, preferably in the life sciences industry.
- Hands-on experience using generative AI platforms and tools (e.g., ChatGPT, Gemini, Claude, or similar).
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