Clinical Data Mapper

Major accountabilities:

• Demonstrates potential for technical proficiency, scientific creativity, collaboration with others and independent thought.
• Under supervision provides input into writing specifications for use cases/demand and necessary reports to ensure high quality and consistent data -Involved in User acceptance testing (UAT) and managing data mapping activities to maintain Clinical Data Warehouse -Under supervision, participates in ongoing review of all data generated from different sources -Supports the development of communications for initiatives.
• Perform hands on activities to conduct data quality assessments.
• Creates under supervision and learns relevant data dictionaries, ontologies and vocabularies -Reporting of technical complaints / special case scenarios related to Novartis data
• Collaborate with other data engineering teams to ensure consistent CDISC based data standards applied
• Be familiar with all clinical study documents from protocol to CSR including Data Management and Biostatistic documents.

Key performance indicators:

• Achieve high level of quality, timeliness, cost efficiency and customer satisfaction across Clinical Data Operations activities & deliverables.
• No critical data findings due to Data Operations-Adherence to Novartis policy, data standards and guidelines -Customer / partner/ project feedback and satisfaction

Minimum Requirements:
Work Experience:

• 3-5 years of experience in working in clinical trials data reporting
• Collaborating across boundaries.
• Knowledge of clinical data
• Availability of sufficient information to find and understand data
• Availability of data quality assessments
• Experience in Agile way of working would be a plus

Skills:

• CDISC SDTM/ADaM Mapping
• Clinical Data Management.
• Experience in being able to work with different legacy, historical, local data standards
• SQL basic knowledges
• Python skills would be a plus
• Able to work in a worldwide team
• Data Privacy
• Data Operations.
• Data Science.
• Databases.
• Detail Oriented.

Languages :

• English.