Clinical Data Manager

SPECTRAFORCE; South San Francisco (CA); On-site; USD 95,000 - 125,000; Full time

Job summary

A leading healthcare organization is seeking a Clinical Data Manager II in South San Francisco, CA. This role involves overseeing data collection, validation, and management while ensuring compliance and data quality across multiple clinical studies. Candidates should have 5–10 years of experience in Clinical Data Management with a relevant degree, and knowledge of ICH-GCP and CDISC standards. Strong analytical and project management skills are essential. This position offers a collaborative environment focused on innovative data solutions aligned with FAIR principles.

Qualifications

• 5–10 years of Clinical Data Management experience required.
• Strong knowledge of ICH-GCP and regulatory requirements.
• Experience with CDISC standards (SDTM preferred).
• Proven project management and stakeholder management skills.
• Experience with Real World Data and advanced data sources.

Responsibilities

• Oversee collection, validation, and curation of clinical and real-world data.
• Manage timelines, risks, and deliverables across multiple studies.
• Ensure successful execution of study scope of work (SOW).
• Apply FAIR principles to optimize data usability and accessibility.

Skills

Clinical Data Management experience

Project management skills

Analytical skills

Problem-solving abilities

Communication skills

Education

Bachelor’s or Master’s degree in Life Sciences, Data Science, Bioinformatics

Tools

SAS

R

Python

SQL

Tableau

Medidata Rave

Oracle Clinical

Job description

We are seeking a Clinical Data Manager II to client USMA Data Management team. This role sits within a highly collaborative environment focused on end-to-end data lifecycle management, supporting exploratory research, clinical development, and evidence generation.

You will act as a data quality leader, ensuring high-quality, compliant clinical data while driving innovative data solutions aligned with FAIR (Findable, Accessible, Interoperable, Reusable) principles.

Key Responsibilities

Data Management & Quality

• Oversee collection, validation, and curation of clinical and real-world data
• Develop and manage clinical databases ensuring accuracy and integrity
• Perform high-level data reviews using visualization and statistical monitoring tools
• Identify trends, anomalies, and gaps in datasets

Study & Project Oversight

• Manage timelines, risks, and deliverables across multiple studies
• Ensure successful execution of study scope of work (SOW)
• Maintain accountability for data quality and regulatory compliance
• Partner with FSPs, CROs, and external vendors to oversee deliverables
• Manage data transfer agreements and ensure adherence to standards
• Collaborate cross-functionally with biometrics, clinical teams, and business stakeholders
• Design and implement fit-for-purpose data solutions
• Support collection of diverse data types (e.g., biomarkers, EMR, sensor data)
• Contribute to enterprise-wide initiatives and emerging technologies
• Apply FAIR principles to optimize data usability and accessibility

Leadership & Technical Expertise

• Provide guidance to data management teams and stakeholders
• Act as SME for data acquisition, standards, and best practices
• Represent Data Management in study team and data quality meetings

Required Qualifications

• 5–10 years of Clinical Data Management experience
• Bachelor’s or Master’s degree in Life Sciences, Data Science, Bioinformatics, or related field
• Strong knowledge of ICH-GCP and regulatory requirements
• Experience with CDISC standards (SDTM preferred)
• Proven project management and stakeholder management skills
• Strong analytical, problem-solving, and communication abilities

Preferred Qualifications

• Experience leading DM activities across multiple clinical studies
• Familiarity with EDC systems (e.g., Medidata Rave, Oracle Clinical)
• Experience with Real World Data (RWD) and advanced data sources
• Proficiency in tools/languages such as SAS, R, Python, SQL
• Experience with data visualization tools (Tableau, Shiny)
• Knowledge of MedDRA, WHODrug, and advanced analytics (AI/ML)
• Exposure to big data tools (Hadoop, Spark)