Senior Associate, Data Manager, Clinical Data Sciences

Use Your Power for Purpose

In this role, you will:

• Contribute to moderately complex projects, managing time effectively to meet targets and develop short-term work plans.
• Take on the role of Data Manager for clinical trials, overseeing Data Monitoring and Management (DMM) activities.
• Collaborate with partners and colleagues to ensure operational excellence and apply standards while developing data cleaning reports.
• Maintain high standards across all DMM deliverables and ensure data quality and completeness as specified in the Data Management Plan.
• Document and share lessons learned during studies to promote cross-study learning.
• Build strong relationships with local and global subject matter experts (SMEs) to leverage their expertise in systems and processes, proactively identifying issues and developing solutions.

Here Is What You Need (Minimum Requirements):

• BA/BS with at least 2 years of experience or MBA/MS with any years of experience
• Demonstrated knowledge of data management processes and principles
• Proficiency in web-based data management systems
• Working knowledge of electronic document management systems
• Familiarity with the International Conference on Harmonization, particularly Good Clinical Practices
• Thorough understanding of clinical study management and regulatory operations processes
• Effective verbal and written communication skills

Bonus Points If You Have (Preferred Requirements):

• Master's degree
• Relevant pharmaceutical industry experience
• Experience using data visualization tools
• Proficient experience using commercial clinical data management systems and/or EDC products
• Awareness of regulatory requirements and relevant data standards
• Strong analytical and problem-solving skills
• Ability to work collaboratively in a team environment
• Excellent organizational and time management skills
• Experience using common AI tools, including generative technologies such as ChatGPT or Microsoft Copilot, to support problem solving and enhance productivity. Demonstrated curiosity for exploring how these tools can improve outcomes and understanding of responsible AI practices, including risk management and ethical use