Clinical Data Science Associate

As we continue to expand our global operations, our established and highly active Clinical Data Science team is now seeking an additional 10 Clinical Data Science Associates! This is a very exciting time to join us and this role has a clear and defined progression path as well as dedicated on the job training to give you the best springboard for a continued successful career in Clinical Data Science.

As a Clinical Data Science Associate you will be trained to lead end to end data review activities performed on a clinical trial, be accountable for achieving clinical data science deliverables on-time, with high- quality and to agreed financial metrics, and communicate trending and summary of findings to internal and external stakeholders to support on-time delivery of data fit for analysis.

Responsibilities:

1. Protocol Understanding – Review and comprehend protocol content, ensuring alignment with clinical data science objectives and regulatory guidelines.
2. Clinical Data Interpretation – Analyze and interpret clinical data, identifying trends, patterns, and outliers to support decision-making in research and development processes.
3. Project Management – Coordinate and support various aspects of clinical data science projects, including data collection, analysis, and reporting, while adhering to timelines and milestones.
4. Financial Tracking – Monitor and track project budgets, expenses, and resource allocations, collaborating with finance and project teams to ensure fiscal responsibility and efficiency.
5. Cross-functional Collaboration – Collaborate with cross-functional teams to integrate clinical data insights into broader research strategies and initiatives.
6. Quality Assurance – Implement quality control measures to ensure accuracy, completeness, and integrity of clinical data, complying with regulatory standards and industry best practices.
7. Documentation and Reporting – Prepare documentation, reports, and presentations summarizing clinical data findings, methodologies, and recommendations for internal stakeholders and regulatory submissions.
8. Continuous Learning – Stay abreast of advancements in clinical data science, healthcare regulations, and industry trends, actively seeking opportunities for professional development and knowledge sharing within the organization.