Job Description
This job is with Novartis, an inclusive employer and a member of myGwork – the largest global platform for the + business community. Please do not contact the recruiter directly.
Summary Location: London, UK; Dublin, Ireland
About the Role:
Complex data are integral to our work in clinical studies. This position will be part of a newly established AI & Data Engineering team within the Advanced Quantitative Sciences function at Novartis. Our mission is to leverage automation and artificial intelligence to unlock the potential of complex scientific data sources. By accelerating quantitative decision-making in clinical trials through high-quality data assets and tools, we aim to bring innovative medicines to patients faster.
The Data Engineering Lead guides and drives the development of robust data assets from both internal and external sources to support data interrogation, research, development efforts, and external collaborations. Collaborating with our quantitative science community, TSC, Statistical Programming colleagues, IT, QA, BR data science teams, and vendors, the Data Engineering Lead ensures the delivery of high-quality, fit-for-purpose data assets, automation pipelines, and related documentation, facilitating scientific advancements in drug development.
Key Responsibilities:
1. Develop data pipelines and IT infrastructure solutions to enable Quantitative Sciences to utilize high-quality datasets for decision-making at trial and project levels, pooling structured data from clinical trials and incorporating evidence from large or multimodal data sources (e.g., genomics, biomarkers, digital tech, sensors, imaging, real-world evidence). Produce high-quality, versioned data assets and software pipelines for reproducible analysis.
2. Provide technical leadership for data engineering projects, from conception to deployment. Define project scope, goals, and deliverables, monitor progress, and adjust plans as needed to meet deadlines.
3. Build strong collaborative relationships and communicate effectively with Quantitative Science partners and clinical teams to foster a culture of open skill-sharing and transparency.
4. Lead in agile engineering and consulting, offering guidance on complex data challenges and unplanned data issues.
5. Focus on risk, quality, and compliance by proposing and implementing process improvements. Ensure all data engineering processes are well-documented and compliant with legal, regulatory, data security, and privacy standards.
6. Stay updated with industry trends, contribute to open-source projects, and participate in external scientific events to strengthen Novartis' presence in the data engineering community.
7. Encourage continuous learning, collaboration, and innovation within the team. Facilitate communication and delegate tasks to meet deadlines effectively.
What you will bring to the role:
1. MSc or PhD in Computer Science/Engineering, Data Sciences, Bioinformatics, Biostatistics, or related computational quantitative field.
2. 4-6+ years developing data pipelines and infrastructure, preferably within drug development or life sciences.
3. Expertise in software/data engineering practices, including versioning, release management, deployment, and agile tools.
4. Strong skills in R, Python, SQL.
5. Knowledge of large-scale data processing technologies (e.g., HPC, distributed computing), databases, cloud or on-prem environments, containerization, distributed storage, and databases.
6. Excellent interpersonal and communication skills, experience working in matrix organizations.
7. Proven track record of high-quality results in quantitative sciences or publications.
8. Experience in AI, Big Data, Data Governance, Data Management, Data Quality, Data Science, Data Strategy, Data Visualization, Master Data Management.
9. Experience with Machine Learning, Python, R, and statistical analysis.
Benefits and rewards:
Learn more about how we support your growth: https://www.novartis.com/careers/benefits
Commitment to & :
We are dedicated to creating an inclusive, diverse work environment that reflects the communities we serve.
Accessibility and accommodation:
We provide reasonable accommodations for individuals with medical conditions. Contact .switzerland@novartis.com with your request, including the job requisition number.
Why Novartis: Join us in transforming patient lives through science and collaboration. More info: https://www.novartis.com/about/strategy/people
Join our Novartis Network: Stay connected and explore new opportunities: https://talentnetwork.novartis.com/network
#J-18808-Ljbffr