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About the role
- Principal Scientist ensuring data quality for R&D Data Science at Johnson & Johnson. Leading quality initiatives and collaborating with cross-functional teams in innovative medicine.
Responsibilities
- Develop and maintain a data quality management framework aligned with GxP, FAIR, and enterprise principles.
- Define data quality dimensions (accuracy, completeness, consistency, timeliness, validity, integrity, and lineage) and establish measurable KPIs.
- Partner with Data Governance, Knowledge Management Global Development, Regulatory and Master Data Management (MDM) teams to ensure traceability and alignment of data quality standards across domains.
- Contribute to data stewardship, defining ownership and escalation procedures for quality issues.
- Lead data validation activities across multiple data types — including clinical, real world, omics, manufacturing, and digital health data.
- Identify and enable the use of tools, driving data quality automation and monitoring.
- Design dashboards and reports to convey key metrics and communicate insights to scientists and leadership.
- Collaborate with AI/ML, Global Functions, Real World Evidence, Clinical Data Management, Global Regulatory, J&J Technology, Epidemiology, and the Commercial organization to understand current quality controls and assess the value / need for subsequent controls.
- Act as the liaison between R&D DSDH and J&J Technology, translating quality requirements into technical rules and data validation workflows.
- Ensure data quality processes align (where applicable) to regulatory and industry standards, including FDA 21 CFR Part 11, GCP, GDPR, HIPAA, and ALCOA+ principles.
- Support audit readiness by maintaining robust documentation and evidence of data quality processes.
- Drive adoption of AI-assisted data quality tools and metadata-driven automation to reduce overhead.
- Stay current on emerging data quality trends in the pharmaceutical and healthcare space.
- Mentor junior quality analysts.
Requirements
- 8 – 10+ years of experience in pharma/biotech R&D or commercial functions, with significant exposure to data management or 6+ years of experience in pharma/biotech R&D or commercial functions with advanced degree.
- Experience in master data management, ontology development, and/or knowledge graph application.
- Understanding controlled vocabularies (e.g., SNOMED CT, MedDRA, LOINC).
- Experience in data profiling and validation, including the use of tools and writing in SQL, Python and/or R.
- Experience integrating data across discovery, development, clinical, regulatory, and/or commercial domains.
- Strong understanding of data standardization and harmonization.
- Experience working with / in validated environments.
- Knowledge of FDA and EMA guidelines, especially around GxP, ALCOA+ data integrity principles, and 21 CFR Part 11 compliance.
- Awareness of CDISC, SDTM, ADaM, HDF5 and H5mu standards.
- Strong writing skills for creating / drafting of quality reports, SOPs and general guidelines.
Benefits
- Health insurance
- 401(k) matching
- Paid time off
- Flexible work arrangements
- Professional development opportunities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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