Senior Regulatory Data Manager, Nicotine Sciences
Listed on 2026-10-29
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IT/Tech
Data Analyst, Data Scientist, Data Warehousing, Data Engineering
Senior Regulatory Data Manager, Nicotine Sciences
Regulatory Data Management | FDA CTP Studies | TPPI, AUS, and Regulated Nicotine Research
About M/A/R/C Research
M/A/R/C Research delivers high-quality marketing, public health, and regulatory research for clients operating in complex and highly regulated categories. Our teams combine rigorous study design, advanced data collection technologies, defensible analytics, and strong quality controls to produce reliable, audit-ready evidence.
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Key Responsibilities Nicotine Sciences Data ManagementLead data management activities for regulated nicotine science studies, including TPPI, AUS, PMSS, consumer perception, intention, behavioral, and related public health research programs.
Translate protocols, statistical analysis plans, survey instruments, and client specifications into clear data management requirements.
Develop and maintain study-specific data management documentation, including Data Management Plans, Data Validation Plans, CRF/eCRF specifications, Data Review Plans, Database Lock Plans, Data Transfer Specifications, and related client-required plans.
Design, review, validate, and support electronic data capture systems, online survey platforms, ePRO/eCOA tools, and other study data collection environments.
Manage study metadata, codebooks, coding standards, edit checks, validation rules, derivation logic, and controlled data specifications.
Oversee database build, configuration support, user acceptance testing, production deployment, and version-controlled documentation.
Data Quality, Compliance, and Inspection ReadinessEstablish and monitor data quality metrics across assigned studies, including completeness, consistency, discrepancy status, query aging, reconciliation status, and database lock readiness.
Conduct routine data review, cleaning, query generation, discrepancy resolution, and exception documentation.
Ensure study data and documentation support applicable regulatory, client, and internal quality requirements, including FDA expectations, 21 CFR Part 11, ICH-GCP where applicable, HIPAA, GDPR where applicable, CDISC standards, and internal SOPs.
Support risk-based quality management, audit readiness, and inspection response activities.
Perform or oversee reconciliation of external vendor data, qualitative coding, laboratory or test data, digital health data, and other ancillary datasets when included in the study scope.
Ensure data accuracy, integrity, security, audit trails, controlled access, and traceable documentation throughout the study lifecycle.
Database Lock, Reporting, and Data TransferCoordinate interim and final database lock and unlock activities, ensuring queries, reconciliation items, and quality exceptions are resolved or documented before lock.
Produce data listings, status reports, data quality dashboards, and study-level data management metrics.
Deliver clean, analyzable datasets and supporting documentation to biostatistics, analytics, clients, sponsors, and regulatory teams.
Support preparation of technical reports, study reports, regulatory submission materials, data transfer packages, and audit responses.
Partner with biostatistics and analytics teams to support CDISC-aligned outputs, including CDASH, SDTM, and ADaM where required by the study.
Stakeholder Collaboration and LeadershipServe as the lead data management representative for assigned nicotine science studies.
Collaborate with clients, sponsors, project managers, research directors, statisticians, data scientists, compliance teams, field operations, technology teams, and external vendors.
Participate in protocol reviews and study design discussions to confirm feasibility, data quality expectations, and downstream reporting requirements.
Provide clear guidance and training on data management processes, system usage, documentation standards, and study-specific requirements.
Communicate data risks, decisions, and status updates in a concise, business-appropriate manner for technical and non-technical stakeholders.
Process Improvement and InnovationContribute to SOP development, controlled document updates, and continuous improvement initiatives for regulated research data management.
Evaluate automation, AI-enabled data review, anomaly detection, and dashboarding opportunities that improve quality, consistency, and efficiency while maintaining appropriate oversight.
Support standards for decentralized data collection, digital endpoints, real-world data, external vendor integrations, and…
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