Digital Infuzion

Senior Quality Analyst, Translational Research

Digital Infuzion

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Job Level

Senior

About the role

  • Serve as subject matter expert evaluating scientific data submissions across the translational research continuum, ensuring the accuracy, completeness, and scientific validity of submissions
  • Review scientific data submissions for accuracy, completeness, and adherence to defined standards
  • Evaluate internal consistency and scientific relevance, ensuring logical coherence and methodological soundness
  • Assess methodological appropriateness of data, with emphasis on pre-clinical and translational research
  • Translate complex workflows into efficient, automatable processes and optimize human-in-the-loop AI for accuracy and oversight
  • Collaborate with domain experts, informatics teams, and data providers to resolve discrepancies and improve data quality
  • Monitor data quality metrics, identify trends, and recommend enhancements to submission guidelines, quality control processes, and the data model
  • Maintain up-to-date knowledge of emerging research methods, data standards, automation technologies, and domain science to advance data quality practices
  • Provide mentorship and direction to Data Quality Analysts, ensuring consistent application of quality standards and fostering professional growth
  • Work closely with the Principal Investigator and Scientific Program Manager to align data quality practices with scientific goals

Requirements

  • Advanced degree (Master’s or PhD) in relevant scientific discipline (e.g., biomedical sciences, bioinformatics, epidemiology, virology, immunology, or related field)
  • Strong understanding of pre-clinical research methods and experimental design
  • Proven experience in assessing and managing data quality in structured scientific environments, including evaluation of data consistency for logical coherence and scientific validity
  • Experience translating scientific and data workflows into process documentation for automation or system optimization
  • Excellent communication skills, with the ability to translate technical findings into actionable recommendations for diverse stakeholders
  • Detail-oriented, with the ability to work independently and collaboratively within cross-disciplinary teams
  • Demonstrated ability to improve processes and systems through observation, feedback, and iteration
  • Preferred: Experience in infectious disease, immunology, or influenza-related research
  • Preferred: Knowledge of controlled vocabularies, ontologies, and data standards in biomedical research
  • Preferred: Understanding of data exchange standards, such as CDISC, HL7, or FAIR principles
  • Preferred: Proficiency with database systems, structured data models, and submission pipelines
  • Preferred: Familiarity with human-in-the-loop AI processes and automation opportunities in data review workflows
  • Preferred: Experience coordinating cross-functional teams or projects in research or data management settings