Clinical Data Manager II
Job in
South San Francisco, San Mateo County, California, 94083, USA
Listed on 2026-07-01
Listing for:
Advanced Clinical
Full Time
position Listed on 2026-07-01
Job specializations:
-
IT/Tech
Data Analyst, Data Engineering, Data Warehousing, Data Scientist
Job Description & How to Apply Below
OVERVIEW
We are currently seeking a highly skilled Clinical Data Manager II to join a well-known client in South San Francisco, CA. This role is responsible for managing the full data lifecycle, supporting exploratory research, clinical development, and evidence generation through high‑quality, compliant data practices.
The Clinical Data Manager will collaborate across functions to design and implement fit‑for‑purpose data management solutions, ensuring adherence to F.A.I.R. principles (Findable, Accessible, Interoperable, Reusable). This position plays a key leadership role in ensuring data quality, vendor oversight, and the delivery of scalable, innovative data solutions that support clinical and research programs.
RESPONSIBILITIES Data Management & Quality Oversight- Design and execute data management strategies aligned with study and program objectives.
- Ensure adherence to F.A.I.R. data principles across all data lifecycle activities.
- Perform high‑level data quality reviews using visualization tools and statistical monitoring techniques to identify trends, anomalies, and gaps.
- Oversee data curation, integration, and standardization across multiple data sources.
- Manage timelines, deliverables, and risk mitigation strategies to ensure successful study execution.
- Provide oversight of Functional Service Providers (FSPs), CROs, and external vendors, ensuring quality and compliance of deliverables.
- Review and manage Task Ownership Matrices (TOMs) and vendor activities.
- Partner with cross‑functional teams on vendor selection and data transfer agreements, ensuring appropriate standards and models are used.
- Serve as a subject matter expert for data collection strategies, including emerging data types (e.g., biomarkers, sensors, EMR/EHR data).
- Drive innovation by recommending new technologies and tools for data acquisition and management.
- Support sample management workflows and eManifest processes, resolving data queries proactively.
- Collaborate with stakeholders across clinical, biometrics, and business teams to align on data strategy and insights needs.
- Represent Data Management in study management meetings and data quality forums.
- Communicate data insights, risks, and progress effectively to stakeholders.
- Provide guidance and mentorship to team members and external partners on data management best practices.
- Contribute to enterprise‑wide and cross‑functional initiatives that enhance data capabilities and tools.
- Support adoption of advanced analytics, visualization, and emerging data technologies.
- Continuously improve processes to enable scalable, efficient, and compliant data management practices.
- Demonstrated experience in clinical data management across the full study lifecycle (startup through database lock/close).
- Strong knowledge of CDISC standards (e.g., SDTM, CDASH) and clinical data structures.
- Experience working in regulated environments (ICH GCP).
- Proven experience managing vendors, CROs, and FSPs in data delivery.
- Experience in data analytics, visualization tools, and data quality monitoring.
- Strong project management experience, including managing multiple priorities and timelines.
- Experience leading data management study teams.
- Experience with real‑world data and/or clinical trial data collection.
- Familiarity with programming languages (SAS, R, Python, SQL).
- Experience with advanced analytics, AI/ML, or big data tools (e.g., Hadoop, Spark).
- Experience with visualization tools (e.g., Tableau, Shiny).
- Bachelor’s or Master’s degree in Life Sciences, Data Science, Bioinformatics, Computer Science, or a related field required.
- Equivalent industry experience may be considered.
- Strong understanding of data lifecycle management in clinical research.
- Excellent communication and collaboration skills across cross‑functional teams.
- Ability to think strategically while executing operational data management tasks.
- Strong analytical mindset with the ability to interpret complex datasets.
- Proven leadership and mentoring…
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