Novartis is looking to build the future of oncology research by shaping early clinical development through innovative biomarker data infrastructure, translational research, and AI-powered discoveries.
Requirements
- Minimum 10 years of hands-on experience architecting and managing clinical data engineering, data management, and bioinformatics solutions in pharmaceutical or biotechnology industry.
- Demonstrated expertise in designing, implementing, and scaling data infrastructure to support clinical development—including Artificial Intelligence (AI) / Machine Learning (ML) -driven analytics and multimodal data integration.
- Proven ability to define, document, and operationalize end-to-end assay data generation and processing pipelines, with a focus on automation, orchestration, and compliance.
- Extensive experience with oncology clinical trials, including regulatory-compliant management of clinical biomarker data and application of data standards (e.g., Clinical Data Interchange Standards Consortium [CDISC], Study Data Tabulation Model [SDTM], Analysis Data Model [ADaM]).
- Deep familiarity with FAIR (Findable, Accessible, Interoperable, Reusable) data principles, data harmonization, and enterprise data governance frameworks.
- Strong leadership in technical teams, with advanced communication and stakeholder management skills.
- Advanced proficiency in cloud-native architectures, data lakes, and visualization frameworks (e.g., RShiny, Dash, Spotfire); strong programming and engineering skills (R, Python, Java, shell scripting, Linux, HPC)
Responsibilities
- Define and implement the clinical data engineering roadmap in alignment with Novartis’ data and digital strategy, collaborating with SMEs and OncDS leadership.
- Integrate advanced tools and AI/ML-ready infrastructure to support predictive modeling, multimodal analytics, and real-world data applications.
- Align clinical and pre-clinical data engineering initiatives with the broader oncology strategy.
- Lead, manage, and develop a high-performing clinical data engineering team, fostering collaboration and growth.
- Drive strategic initiatives and partnerships across a matrixed organization.
- Oversee data ingestion, transformation, and validation processes for clinical trial data, ensuring compliance with GCP/GxP, CDISC, and SOPs.
- Build and optimize data pipelines for both structured and unstructured clinical data to enable advanced analytics and informed decision-making.
Other
- Master's degree in computer science, Bioinformatics, Data Engineering, Software Engineering or a closely related discipline; PhD preferred.
- 0-3% travel as defined by the business (domestic and/ or international).
- Strong leadership and stakeholder management skills.
- Ability to work with and provide reasonable accommodation to individuals with disabilities.
- US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits.
