When our values align, there's no limit to what we can achieve.
 
At Parexel, we all share the same goal - to improve the world's health. From clinical trials to regulatory, consulting, and market access, every clinical development solution we provide is underpinned by something special - a deep conviction in what we do.

Each of us, no matter what we do at Parexel, contributes to the development of a therapy that ultimately will benefit a patient. We take our work personally, we do it with empathy and we're committed to making a difference.

The Data Surveillance Analyst (DSA) is responsible for analyzing scientific and operational data to support the Data Surveillance process and reviewing project-specific Quality Tolerance Limits. They assist in developing Data Surveillance Plans (DSPs) and conduct defined project reviews. The Data Surveillance Analyst also attends internal and external Data Surveillance meetings, where they present relevant findings to the project team.

Key Accountabilities:
 

Data Surveillance Plan Development and Technology Configuration:

• Support the development of a robust Data Surveillance Plan, including Key Risk Indicators, Quality Tolerance Limits, and central statistical analysis
• Configure and maintain Data Surveillance technologies (e.g., Clue Points Central Monitoring Platform).
• Create data import mapping for all data sources.
• Create and set-up standard and bespoke KRIs.
• Create and set-up statistical analysis parameters.
   

Data Surveillance Review:

• Review relevant data via the scoped technologies and additional sources as required to support reviews designated for the Data Surveillance Analyst per the project specific Data Surveillance Plan, including project specific Quality Tolerance Limits.
• Document findings from Data Surveillance activities in the DS Findings Form, Issue Tracking system(s) and other as appropriate.
• Provide feedback and work with Technology teams to identify potential solutions that match the business and technology strategy.
• Apply working knowledge and judgment to identify and evaluate potential data quality trend, outliers and emergent issues. Determine and implement appropriate follow-up action with the input of other / relevant parties and / or guidance provided, if applicable.
• Actively participate in Investigator and other external or internal meetings and audits & regulatory inspections as required. 
• Recognize impact of study non-compliance/issues/delays/data quality signals and communicate/promptly escalate to FL any site and/or study issues that require immediate action.
• Maintain a positive, results orientated work environment, building partnerships and collaborative relationships, communicating with team(s) in an open, balanced, objective manner, modeling the HPC values.
• Work with team members to meet project goals and encourage the support of team members where required.
• Maintain a working knowledge of and ensure compliance with applicable ICH-GCP Guidelines, international and local regulations, Parexel SOPs, other Parexel / Sponsor training requirements and study.
• Refresh technologies for each review cycle per DS Plan
• Perform core reviews per DS Plan
• Document instances of atypical data per DS Plan
• Collaborate with DS Team Members to correlate findings from various sources
• Support PL with DS Review meeting, driving reviews and decisions as needed and agreeing on actions.
• Engage DS Team to compile signals/actions into client ready list.
• Support documentation of actions in Clue Points Issue Management system.
• Complete, share, and file Central Monitoring Report.

Skills:

• Comprehensive knowledge of Parexel RBQM processes and data surveillance methods
• Familiarity with centralized monitoring and Data Driven Monitoring practices
• Proficient in data analysis, trend identification, and issue triage
• Basic understanding of SDTM domains and data operations concepts
• Basic SAS programming skills
• Proficient in relevant software: CTMS, EDMS, MS Office
• 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

Knowledge and Experience: 

• 2 or more years of relevant medical, clinical or data management work experience recommended
• 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

Education:

• Educated to a degree level (medical, biological science, pharmacy and/or data analytics, preferred) or relevant clinical, technology or business equivalent