Senior Clinical Data Science Programmer
About the Role: This is a pivotal position in developing and implementing programming solutions to support the analysis and reporting of clinical trial data. You will contribute to the advancement of innovative treatments and therapies by ensuring the accuracy and efficiency of data processing through your programming expertise.
Key Responsibilities
* Develop, validate, and maintain programming solutions for CDMS (EDC systems such as Rave / Veeva), data validation outputs, data review / risk management outputs, custom reports, and programs in clinical trials.
* Collaborate with data managers, project managers, clinical data scientists, and biostatisticians to ensure the integration of programming solutions into the overall data management process.
* Act as a primary point of contact during the study set up and maintenance phase for system programming related questions by the project team.
* Support colleagues with the clinical trials environment and concepts of Clinical Data Management Systems.
* Perform extracts of data from CDMS and creation of data transfer programs.
* Act as mentor and provides guidance and support to more junior programmer levels assigned to a project.
* Assist in the development and implementation of improvements to technical systems and processes within an SME role.
* Provide guidance on programming best practices, coding standards, and data quality control measures.
* Stay updated on advancements in programming languages and data management tools to enhance operational efficiencies.
What We Offer
A challenging and rewarding career opportunity that will allow you to grow professionally and personally. Our team is passionate about delivering high-quality results, and we are committed to helping you achieve your goals.
Requirements
* Strong programming skills, with experience in CDMS (EDC systems such as Rave / Veeva).
* Excellent collaboration and communication skills.
* Ability to work in a fast-paced environment and adapt to changing priorities.
* High level of analytical and problem‑solving skills.
* Strong knowledge of data management principles and practices.
* Experience with data validation and risk management.
* Strong understanding of data quality control measures and programming best practices.
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