Senior Regulatory Data Manager, Nicotine Sciences

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.

#LI-Remote

Position Summary

The Senior Regulatory Data Manager, Nicotine Sciences, leads the planning, implementation, validation, quality review, and delivery of regulated study data for nicotine and tobacco product research. This role supports Tobacco Product Perception and Intention (TPPI) studies, Actual Use Studies (AUS), Post marketing Surveillance Studies (PMSS), and other related FDA Center for Tobacco Products (CTP) research programs. The position serves as the primary steward of study data from protocol review through database lock, final reporting, and client-ready regulatory deliverables.

The role requires strong regulatory data management discipline, a practical understanding of survey and electronic data capture environments, and the ability to translate protocol requirements into controlled data collection, review, transfer, and reporting processes. The ideal candidate can work across project management, research, compliance, biostatistics, analytics, field operations, clients, sponsors, and external vendors while maintaining data integrity, inspection readiness, and operational efficiency.

Key ResponsibilitiesNicotine Sciences Data Management

• Lead 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 Readiness

• Establish 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 Transfer

• Coordinate 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 Leadership

• Serve 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 Innovation

• Contribute 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 sponsor data transfers.
• Promote best practices aligned with SCDM Good Clinical Data Management Practices and CDISC implementation guidance.

• 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 product research, public health research, healthcare research, pharmaceutical research, biotechnology, medical device, CRO, or FDA-related studies.

• Strong understanding of regulated study processes, data management principles, data validation, data quality controls, audit readiness, and applicable regulatory frameworks.
• Hands-on experience with EDC, eTMF, survey, or clinical data platforms such as Decipher, Medidata Rave, REDCap, Oracle Clinical, Veeva, TrialKit, MEDRIO, or similar systems.
• Working knowledge of SQL, SAS, Power BI, and data visualization or reporting tools.
• Ability to create clear data management documentation, quality reports, issue logs, decision records, and sponsor-facing deliverables.
• Strong analytical, organizational, communication, and problem-solving skills.

Preferred Qualifications

• Experience supporting FDA submissions, pivotal studies, TPPI studies, AUS studies, PMSS or other FDA CTP-relevant nicotine and tobacco product research.
• Knowledge of CDISC standards, including CDASH, SDTM, and ADaM.
• Experience with ePRO/eCOA, online survey data, consumer research data, qualitative coding data, or mixed-methods study data.
• CCDM certification or another relevant clinical data management, regulatory, quality, or analytics certification.
• Experience managing external vendors, data integrations, data transfer specifications, and controlled data handoffs.
• Familiarity with real-world evidence sources, electronic health records, decentralized studies, digital endpoints, and AI-enabled data review technologies.

Success Factors

• Data integrity mindset: Maintains meticulous attention to accuracy, completeness, traceability, and documentation.
• Regulatory discipline: Understands that study data must be defensible, inspection-ready, and suitable for client regulatory use.
• Nicotine science focus: Applies data management rigor to tobacco and nicotine research questions, including perception, intention, behavior, and actual use outcomes.
• Cross-functional communication: Explains data issues, risks, and decisions clearly to technical and non-technical audiences.
• Operational ownership: Drives data management activities from study startup through closeout, database lock, and final deliverable transfer.
• Continuous improvement: Identifies ways to improve quality, efficiency, consistency, and automation while preserving human oversight and compliance.

• M/A/R/C® is committed to providing an exceptional work environment and excellent benefits.
• Health Care Plan (Medical, Dental, Vision & Supplemental)
• Retirement Plan (401k with Company Match)
• Profit Sharing
• Paid Time Off (Vacation, Sick & Public Holidays)
• Family Leave (Maternity, Paternity)
• Training & Development