Virtusa Corporation is a globally recognized digital engineering and IT services provider, delivering innovative solutions to help businesses accelerate their digital transformation. With a strong presence in healthcare and life sciences, Virtusa is committed to revolutionizing clinical data management and analytics. The company provides cutting-edge technology solutions that enhance efficiency, accuracy, and compliance in clinical trials.
Responsibilities in Job
As a Clinical Programmer at Virtusa, your key responsibilities will include:
- Creating a catalog of reports to aid data cleaning activities, ensuring data integrity.
- Automating manual checks, reconciliations, and edit checks for Third-Party Vendor (TPV) data.
- Developing tools and repositories to minimize data errors at the source, especially for lab reference ranges.
- Programming reports to identify missing pages and detect errors at the subject level.
- Generating reports and visualizations to assess data cleaning status and track discrepancies in Electronic Data Capture (EDC) and TPV data.
- Collaborating with cross-functional teams, including data management, development operations, clinical, and biometrics, to meet end-user reporting needs.
- Implementing cross-functional projects that align with the clinical programming roadmap.
Qualifications
To be eligible for the Clinical Programmer role, candidates must possess:
- A Bachelor’s degree or equivalent in Computer Science, Life Sciences, or Statistics.
- Strong programming expertise in SAS, Python, R, or SQL.
- Prior experience with business intelligence tools such as Power BI, MicroStrategy, Spotfire.
- A good understanding of data collection and industry data standards.
- Familiarity with EDC systems like Medidata Rave, Inform, or Veeva.
- Basic knowledge of the clinical development process and clinical trial lifecycle.
Required Skills
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The ideal candidate should have expertise in:
- Programming: Proficiency in Python, SAS, and SQL.
- Data Visualization & Analytics: Experience in MicroStrategy, Power BI, or other BI tools.
- Clinical Data Management Tools: Exposure to Saama, SAS LSAF (desirable).
- Domain Knowledge: Understanding of clinical trial lifecycle and data management processes.
