Job Description Summary
Novartis has embraced a bold strategy to drive a company-wide digital transformation. Our objective is to position Novartis as an industry leader by proactively adopting digital technologies that foster innovative approaches to hasten drug discovery and development.
A new role, Global Head of Digital, Information and Artificial Intelligence in Biomedical Research (BR), has been established to spearhead our digital, information technology and AI initiatives in drug discovery and early clinical development ensuring our digital strategy, technologies, skills, and culture are aligned with our objectives while promoting unity and cooperation with key internal and external partners.
This role will involve the leadership and management of around 300+ associates across the globe (including teams in US, Switzerland, Ireland and India) responsible for BR Informatics (RX) and AICS (AI & Computational Sciences) with significant budget responsibilities. RX is responsible for all research IT systems across BR including digital products and software solutions for drug discovery research. RX and AICS partner with drug discovery teams and ensures that BR science keeps up with the rapidly evolving ecosystem of digital and AI technologies by connecting with leaders in academia and industry.
The leader will be a member of BR’s Computational Sciences Council (CSC) and a matrixed member of the Data, Digital, and IT (DDIT) leadership team. It will also represent BR in the governance and strategy setting of AI across Novartis. The role reports into the Chief Data & Digital Officer, BR and will work closely with the Data 42 team.
Job Description
AI & computational science leadership:
Research Informatics & Data Management leadership:
Organizational & people leadership:
Education:
Experience:
Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve
Skills Desired
Agile (Programming Methodology), Artificial Intelligence (AI), Cluster Analysis, Computer Science, Data Engineering, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Data Visualization, Deep Learning, Machine Learning (Ml), Machine Learning Algorithms, Master Data Management, Mentorship, Nlp (Neuro-Linguistic Programming) And Genai, Statistical Modeling, Time Series Analysis, Visualization
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