Data Surveillance Analyst
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Job Description
Data Surveillance Analyst analyzing clinical and operational data for Parexel’s clinical development solutions. Developing surveillance plans, identifying quality signals, and supporting global project teams.
Responsibilities:
- Analyze scientific and operational data to support the Data Surveillance process
- Review project-specific Quality Tolerance Limits
- Assist in developing Data Surveillance Plans (DSPs)
- Conduct defined project reviews
- Attend internal and external Data Surveillance meetings and present relevant findings to the project team
- Support development of Data Surveillance Plans, including Key Risk Indicators, Quality Tolerance Limits, and central statistical analysis
- Configure and maintain Data Surveillance technologies, including creating data import mappings, KRIs, and statistical analysis parameters
- Review relevant data using scoped technologies and additional sources according to project-specific plans
- Document findings in DS Findings Forms, issue tracking systems, and other appropriate systems
- Work with Technology teams to identify solutions aligned with business and technology strategy
- Identify and evaluate data quality trends, outliers, and emergent issues; determine and implement follow-up actions
- Participate in investigator meetings, external and internal meetings, audits, and regulatory inspections as required
- Escalate site and study issues requiring immediate action
- Perform core reviews and document atypical data per the Data Surveillance Plan
- Collaborate with Data Surveillance Team Members to correlate findings from various sources
- Support Project Leads with Data Surveillance review meetings, reviews, decisions, and actions
- Compile signals and actions into client-ready lists
- Support documentation of actions in the CluePoints Issue Management system
- Complete, share, and file Central Monitoring Reports
Requirements:
- University degree (medical, biological science, pharmacy, and/or data analytics)
- Fluent English
- Hands-on programming experience in SAS, R, and/or SQL is a must-have
- Experience with Risk-Based Quality Management (RBQM) processes and data surveillance methods
- Familiarity with centralized monitoring and Data Driven Monitoring practices
- Proficient in data analysis, trend identification, and issue triage
- Proficient in relevant software: CTMS, EDMS, MS Office
- Basic understanding of SDTM domains and data operations concepts
- Experience with CluePoints would be a strong asset
- Client-focused with strong quality orientation
- Effective in matrix and global virtual team environments
- Excellent interpersonal and communication skills, including presentation abilities
- Strong time management and multitasking capabilities
- Ability to work independently with minimal supervision
- Applicants must be based in one of the eligible locations
Benefits:
- Professional growth and development opportunities
- Work-life balance
- Flexible working hours
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