Senior Regulatory Data Manager, Nicotine Sciences
New
M
M/A/R/C ResearchNicotine Science Research
RemoteFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- At least 5 years of clinical, regulatory, or research data management experience in a regulatory environment.
- Required Skills
- SQLMicrosoft Power BIData management
Requirements
- Bachelor's or advanced degree in Life Sciences, Health Informatics, Biostatistics, Epidemiology, Public Health, Computer Science, Data Science, or a related field.
- At least 5 years of clinical, regulatory, or research data management experience in a regulatory environment.
- Experience supporting nicotine science, tobacco research, public health, healthcare, pharmaceutical, or biotechnology studies.
- Strong understanding of regulated study processes, data validation, and audit readiness.
- Hands-on experience with EDC, eTMF, or survey systems (e.g., Decipher, Medidata Rave, REDCap, Oracle Clinical, Veeva, TrialKit, MEDRIO).
- Working knowledge of SQL, SAS, and Power BI.
- Ability to create clear data management documentation and sponsor-facing deliverables.
- Strong analytical, organizational, and communication skills.
- Experience managing external vendors and data integrations.
- Knowledge of CDISC standards (CDASH, SDTM, ADaM) is preferred.
- CCDM or relevant industry certification is preferred.
Responsibilities
- Lead data management activities for regulated nicotine science studies including TPPI, AUS, and PMSS programs.
- Develop and maintain critical study documentation such as Data Management Plans, Data Validation Plans, and Data Transfer Specifications.
- Design, validate, and manage electronic data capture systems, survey platforms, and ePRO/eCOA tools.
- Monitor data quality metrics and conduct routine cleaning, query generation, and discrepancy resolution.
- Coordinate database lock/unlock activities and prepare final datasets and documentation for regulatory submission.
- Collaborate with project managers, biostatisticians, and external vendors to ensure alignment on protocol requirements.
- Identify and implement process improvements including automation and AI-enabled data review technologies.
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