Data Quality Analyst (Translational Research)

• Outcomes First: Focusing on what matters most and making timely, informed decisions.
• Innovative: Embracing creativity and continuous improvement to drive novel solutions.
• Radical Candor: Communicating openly and honestly, balancing direct feedback with genuine care.
• Never Satisfied: Pursuing excellence and continuous growth beyond the status quo.
• Resilient: Adapting and persevering through challenges, turning obstacles into opportunities.

If you’re passionate about leveraging technology to improve healthcare and want to work in an environment that values innovation and collaboration, we may have just the opportunity for you., The Data Quality Analyst will play a key role in evaluating scientific data submissions across the translational research continuum, ensuring accuracy, completeness, and adherence to established standards. This role requires attention to detail, familiarity with pre-clinical research concepts, and an interest in applying best practices to evolving areas of biomedical research, including influenza and infectious disease., * 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.
• Support the translation of data workflows into transparent, structured processes that can be adapted 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.

• 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., * Master’s degree in a relevant scientific or data-related field.
• Understanding of controlled vocabularies, ontologies, and biomedical data standards.
• Familiarity with database systems, structured data models, or data submission pipelines.
• Exposure to human-in-the-loop AI processes and automation in data review workflows.
• Experience with quality control, process improvement, or research data management.

3.4 Remote $65,000 - $80,000 a year - Full-time