Senior Principal Solution Architect, Clinical Data Analytics & Technology

• Lead the design and continuous improvement of Central Monitoring platform configurations and dashboards.
• Develop and govern Key Risk Indicators, Quality Tolerance Limits, risk signals, and statistical monitoring models/ DQA.
• Draft Central monitoring platform specification and refer clinical protocol, CRF, Study ALS and vendor data transfer specification.
• Platform setup, quality control, validation, and go-live readiness across the assigned trials ( 3-5 studies).
• Partner with Clinical, Central monitoring, data management, biostatistics and technology teams to deliver effective analytics strategies.
• Provide technical leadership for data integration, risk analytics, visualisation, troubleshooting, and platform performance.
• Drive automation, standardisation, artificial intelligence, machine learning, and advanced analytics across monitoring operations.
• Mentor Risk-Based Quality Management Data Analysts and strengthen organisational capability through coaching and knowledge sharing.

• More than nine to eleven years of relevant experience in the pharmaceutical, biotechnology, clinical research, or healthcare technology industry.
• Extensive experience in Risk-Based Quality Management and clinical data analytics supporting global clinical trials.
• Hands-on experience configuring Central Monitoring platforms, such as CluePoints or an equivalent Risk-Based Quality Management system.
• Demonstrated experience developing and governing Key Risk Indicators, Quality Tolerance Limits, risk signals, and statistical monitoring models (DQA).
• Strong understanding of clinical trial data, centralised monitoring methodologies, data integration, and clinical data-quality oversight.
• Experience mentoring technical or analytics professionals and providing leadership across cross-functional clinical study teams.
• Strong knowledge of International Council for Harmonization E6(R3), risk-based monitoring principles, and clinical trial quality management.
• Proven ability to deliver process improvement, automation, innovation, and scalable analytics solutions within a regulated environment.
• Interpret protocols, monitoring plans, quality plans, critical data, endpoints, CtQ factors, risks, and study-specific needs
• Understanding ingestion, harmonization, mapping, transformation and data from different sources like EDC, CTMS, IRT/IWRS, laboratory and other third-party data
• Use SAS, SQL, R, Python or equivalent languages for data manipulation, analytics, automation, and troubleshooting
• Manage setup, go-live, refreshes, change requests, protocol amendments, troubleshooting, and study closeout/archival activities
• Deliver assigned work on time and to first time-right quality standards.

• Experience applying artificial intelligence and machine learning to clinical risk detection and monitoring.
• Advanced experience with data visualisation, analytics dashboards, and statistical monitoring methodologies.
• Experience ensuring technology and analytics solutions comply with Good Practice quality requirements and healthcare data-privacy regulations.
• Experience establishing technical standards, governance frameworks, and best practices across a global clinical portfolio.

Why Novartis

Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients' lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture

Benefits and Rewards

Learn about all the ways we'll help you thrive personally and professionally. Read our handbook (PDF 30 MB)

Skills Desired

Classification Methods, Clinical Trials, Computer Data Storage, Computer Programming, Data Analysis, Data Reporting, Data Structures, Programming Languages, Statistical Analysis, Taking Initiative