Principal Clinical Data Scientist

About the role

Novartis is looking for a Principal Clinical Data Scientist in Hyderabad. The role manages data management, coding, clinical data definition (CDD) and data analysis plan (DAP) aspects of several studies, a medium to large project or project-level activities, and acts as a strategic partner with stakeholders so that drug development plans are delivered on time and to a high standard. It also involves designing scalable training delivery models and platforms.

Key responsibilities

• Lead functional activities for medium to large projects in phase I to IV clinical studies within the Global Development organization.
• Coordinate the work of Data Managers, internally and externally.
• Make data management decisions and propose strategies at study or project level.
• Ensure consistent data management processes, increasing standardization and documentation across programs.
• Provide and implement data management solutions and share knowledge.
• Lead process and training deliverables across platforms, franchises or therapeutic areas, including training strategies and knowledge retention.
• Represent Data Operations in audits and inspections, centralizing audit preparation and response.
• Take part in reviewing clinical research protocols, reports and statistical analysis plans, and lead quality deliverables across platforms.

Required profile

• Proven experience in clinical data management, data architecture, data governance, data integration, data profiling, data quality, data science, data strategy and master data.
• Strong project management skills, able to handle multiple tasks and projects at once.
• Cross-cultural experience and broad functional coverage in clinical data management.
• Ability to spot and resolve protocol issues affecting database design, data validation and analysis/reporting.
• Excellent communication and interpersonal skills with cross-functional teams.

Required skills

• Clinical data management, data architecture, data governance, data integration, data profiling, data quality, data science, master data.
• Waterfall model.
• Data management tools used to generate listings for data review and share them with study teams.