Digital Infuzion

Review and assess scientific data submissions for accuracy and consistency, support data quality workflows, collaborate with teams to improve data quality, and contribute to documentation and process improvements. | Bachelor’s degree in a relevant scientific or data-related field, familiarity with pre-clinical research methods, strong attention to detail, communication skills, and collaborative mindset; preferred qualifications include advanced degree and experience with biomedical data standards and AI-assisted workflows. | Description: • Review scientific data submissions for completeness, accuracy, and adherence to defined standards • Evaluate the consistency and scientific relevance of data and flag potential issues for review • Assess methodological details of pre-clinical and translational research submissions under the guidance of senior staff (Data Quality Manager and Scientific Program Manager) • Support the translation of data workflows into transparent, structured processes adaptable for automation and AI-assisted review • Collaborate with scientific staff, informatics teams, and data providers to resolve discrepancies and improve data quality • Assist in monitoring data quality metrics and document trends or recurring issues • Maintain up-to-date knowledge of emerging research methods, data standards, and automation tools to support improvements in data quality practices • Contribute to team documentation and process refinement efforts as part of continuous improvement initiatives Requirements: • Bachelor’s degree in a relevant scientific or data-related discipline (e.g., biomedical sciences, bioinformatics, epidemiology, virology, immunology, or related field) • Familiarity with pre-clinical research methods and experimental design • Strong attention to detail with the capacity to identify inconsistencies or gaps in structured scientific data • Ability to follow established data quality workflows and contribute to process documentation • Strong written and verbal communication skills, with the ability to summarize findings clearly • Collaborative mindset, with the willingness to seek guidance and work effectively in a cross-disciplinary team • Preferred: Master’s degree in a relevant scientific or data-related field • Preferred: Understanding of controlled vocabularies, ontologies, and biomedical data standards • Preferred: Familiarity with database systems, structured data models, or data submission pipelines • Preferred: Exposure to human-in-the-loop AI processes and automation in data review workflows • Preferred: Experience with quality control, process improvement, or research data management Benefits: • Remote-eligible position • We can provide reasonable accommodation to applicants with disabilities • Creative, open, and growth-oriented environment • Opportunity to build expertise at the intersection of data quality, scientific research, and informatics