Clinical Data Specialist - CEDENT

In this role, you will work with the Clinical Data team to interpret and organize clinical oncology data. Reporting to the Clinical Data Manager, you will develop real-world data variables from structured and unstructured sources, design data capture forms, and establish procedures for data abstraction. You will lead feasibility testing to refine data capture methods and implement data validation checks to ensure quality. Collaboration with team members on data model improvements will be a key aspect of the role.
 

• Serve as a clinical data expert for a portfolio of real-world data deliverables.

• Manage and execute data management activities throughout a product's lifecycle, including data model development, data processing (e.g., abstraction, machine learning), design of data capture forms, quality check logic, and guidance for quality check resolution.

• Identify opportunities for product enhancements based on client feedback, industry trends, regulatory changes, and data challenges.

• Plan and conduct feasibility experiments for variable development, recommending optimal design, data sources, and production efficiencies.

• Develop and maintain internal and external guidance for real-world data variables.

• Improve workflows by identifying process enhancements, collaborating with stakeholders, and implementing solutions (e.g., tooling, templates).

• Ensure documentation audit-readiness in line with procedures and applicable data standards.
   

• 2+ years in clinical data management, clinical or lab research, or similar experience in the medical device or pharmaceutical industry.

• Experience with clinical databases (EDCs, EMRs, etc.), knowledge of health data standards (CDISC, MedDRA), and familiarity with SQL, SAS, R, Python, or data analysis platforms (PowerBI, SPSS, Tableau).

• Understanding of clinical research, clinical trials, and regulatory requirements (ICH GCP, 21CFR11, HIPAA).

• Strong project management, organizational, analytical, and communication skills; ability to work in a fast-paced, dynamic environment.

• Bachelor’s or Master’s degree in a science or healthcare-related field, or equivalent experience.

• Foundational knowledge of statistics and experimental design.
   

• Familiarity with cancer treatment and terminology.

• Experience managing data for real-world evidence programs or registries.

• Knowledge of machine learning model development.

• Advanced degree in biomedical science, informatics, or biostatistics.
   

This hybrid role combines remote work with three office days per week.