Senior Clinical Data Mapper

Summary

• Provide timely & professional ongoing Mgmt of Data Operations on Use Cases/Demand deliverables and of clinical data warehouse maintenance with respect to cost, quality and timelines within Clinical Pipeline team. Help developing content and redefining training modules into engaging & interactive applications for Clinical Data Mapper onboarding. Leverage AI-based Clinical Pipeline technology to ensure process simplification and training delivery. Follows data privacy, data-handling procedures and guidelines. Participates in the discussion with Data Scientist/ Data Services or other stakeholders requesting for legacy data mapping effort and translate their needs into data operations. Drives participation and input within Data Operations (DO) in the delivery of quality data and tools, processes and documentation. Manage data Load, Transfer from Novartis Clinical Data Lake and conform of Clinical trial data to SDTM/ADaM compliant standards within the Clinical Data Warehouse. The position is a key contributor with Clinical Pipeline team in ensuring that use case/demands are executed efficiently with timely and high quality deliverables.
  
  

About The Role

Major accountabilities:

• Provides data mapping leadership across assigned use cases/demands and acts as the Clinical Data Mapper Lead where needed -Demonstrates a business understanding of the use cases/demands profile to identify and assist in successful application of data operations processes.
• Manage task allocation of the Clinical Data Mapper in accordance with priorities defined by Clinical Data Operations Lead.
• Recognize and resolve conflicts in data flows or data standards decisions and be responsible to define new quality checks/ validation process to ensure data compliance.
• Participation for all aspects of the Process and Training to ensure full compliance to all applicable global regulatory requirements including data privacy and business objectives are achieved.
• Responsible and accountable to ensure consistency of assigned tasks related to data mappings, maintenance of relevant clinical data and metadata catalogs.
• Build or contribute to relevant data dictionaries, ontologies and vocabularies.
• Perform hands on activities to conduct data quality assessments.
• Supports and assists Clinical Data Mapper staff for assigned use cases/demands -Provides effective input into Data Operations initiatives and innovations for quality, efficiency and continuous improvement in scientific and operational excellence
• Serves as primary Data Mapper ensuring timely and quality deliverables by establishing and maintaining strong working relationships with data mapper teams, and functional lines.
• Acts as a CDISC SDTM/ADaM expert as required
• Discuss with Data Scientists to provide overview on the data mapping process and data related complexities & issues to be resolved.
• Lead independently or participate in improvement initiatives related to the development of the Clinical Pipeline technology
• Collaborate with Data Engineering team to submit advanced data mapping requirements for complex transformation within the Clinical Pipeline.
• 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 Data Operations activities and deliverables.
• No critical audit findings due to Data Mgmt -Adherence to Novartis policy and guidelines -Customer / partner/ project feedback and satisfaction
  
  

Minimum Requirements

Work Experience:

• 5+ years of experience working with Clinical data
• Strong CDISC knowledge (SDTM/ADaM)
• Good knowledge of Clinical Data Lifecycle
• Being able to work with different standards
• Data Privacy knowledges
• Cross Cultural Experience.
• Functional Breadth.
• Experience in Agile way of working would be a plus.
• Project Management.
  
  

Skills

• Clinical Data Management.
• Data Governance.
• Data Integrity.
• Data Operations.
• Data Quality.
• Data Privacy
• Databases.
• Project Management.
• SAS/SQL knowledge
• Python would be a plus
• Artificial Intelligence (Optional)
  
  

Languages

• English.
  
  

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