Data Surveillance Analyst
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Job Description
Data Surveillance Analyst analyzing scientific and operational data for Parexel’s clinical research solutions. Supporting Data Surveillance processes and developing plans across multiple studies.
Responsibilities:
- Analyze scientific and operational data to support the Data Surveillance process and reviewing project-specific Quality Tolerance Limits.
- Assist in developing Data Surveillance Plans (DSPs) and conduct defined project reviews.
- Attend internal and external Data Surveillance meetings, where they present relevant findings to the project team.
- Support cross-functional study team with expertise of Data Surveillance Process and supporting technologies.
- Support the development of a robust Data Surveillance Plan, including Key Risk Indicators, Quality Tolerance Limits.
- Configure and Maintain Data Surveillance technologies (e.g., Clue Points Central Monitoring Platform).
- Review relevant data via the scoped technologies, identifying findings related to trends, outliers, emerging risks, and systemic issues.
- Document findings from Data Surveillance review.
- Provide feedback and work with Technology teams to identify potential solutions that match the business and technology strategy.
- Perform presentations explaining identified findings to internal cross-functional study team and client team.
- Actively participate in external or internal meetings and audits & regulatory inspections as required.
Requirements:
- Min. 2 to 3 years of relevant medical, clinical or data management work experience.
- Experience of working within an adaptive monitoring design study, and/or participating in a Central Monitoring/Data Surveillance process highly recommended.
- Basic SAS programming and/or SQL script writing required.
- Experience with CluePoints system required.
- Educated to a degree level (medical, biological science, pharmacy, and/or data analytics, preferred).
- Fluent English – spoken & written.
- Familiarity with centralized monitoring and Data Driven Monitoring practices.
- Proficient in data analysis, trend identification, and issue triage.
- Knowledge of programming languages highly recommended.
- Risks management and control, quality management and assurance experience preferred.
- 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.
Benefits:
- Flexible work arrangement
- Competitive financial packages
- Training and development
- Smooth induction and training program
- Healthy work/life balance
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