New

Group Head AI Methods (RX & AI and Computational Sciences)

Novartis Group Companies
United States, New Jersey, East Hanover
1 Health Plaza (Show on map)
Oct 21, 2025
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. By utilizing both internal and external R&D data with the power of data science, predictive models, generative AI, and machine learning, our objective is to identify new targets, create more effective therapeutic molecules, better predict drug pharmacokinetics and safety risks, refine clinical trial design, and significantly shorten development cycles. The AICS team leads BR in exploring and applying advanced AI and ML methodologies to generate novel drug discovery insights, and to speed and improve drug discovery efficiency whilst focusing on patients' needs. AI & Computational Sciences (AICS) partners with drug discovery teams, raises the level of AI expertise across Biomedical Research (BR) and ensures that BR science keeps up with the rapidly evolving ecosystem of AI technologies by connecting with AI leaders in academia and industry. This role leads the AI Methods group within AICS and is tasked with leading a group of scientists with significant expertise and experience in building, fine-tuning optimizing state-of-the-art (SOTA) AI algorithms models that can be applied to aid key domains areas of biomedical research that potentially leads to better drugs, faster. Job Description Purpose of the role AI Methods Group Lead: Lead a team of AI researchers who specialize in methodological improvisations of AI models Work with AI modelers to ensure models are robust and performant Work with Engineering and Product Development resources to ensure scalability of training and applicability of models Raise the awareness of AI applications to aid in answering key research questions across BR Help position AI-aided drug discovery contributions to deliver and support progress of BR's portfolio, enable new kinds of therapeutic discoveries, shorten cycle times, and increase efficiency. Collaboration & partnership Act as the primary subject matter expert across BR for building, analyzing and recommending usage of SOTA AI algorithms and models Regularly communicate, engage, align with AICS teams, broader data science community, and senior scientists. Initiate and lead key high-value internal collaborations across BR. Help in bringing synergies on in-housing of SOTA AI models the application of which can bring tangible impact in collaboration with BR DAs and FAs. What you'll bring to the role: 10+ years of significant experience in innovation, development, deployment and continuous support of Machine Learning data management and modeling Expertise in AI algorithmic development and research preferably in biomedical sciences for drug discovery Passion for understanding emerging technologies with pragmatic insight into where those technologies can be integrated into business solutions Ability to balance requirements, manage expectations, and drive effective results using a proactive attitude towards identifying and resolving issues Entrepreneurial spirit with can-do, pro-active attitude Strong organizational, problem-solving, and influencing skills and demonstrated track record of exceptional teamwork Excellent interpersonal, communication, and presentation skills Ability to execute and prioritize well in a complex matrixed environment. Operational and functional leadership Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve. Skills Desired Applied Mathematics, Artificial Intelligence (AI), Aws (Amazon Web Services), Big Data, Building Construction, Cloud Computing, Computer Science, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Electrical Transformer, Machine Learning (Ml), Master Data Management, Professional Services, Python (Programming Language), R (Programming Language), Random Forest Algorithm, Statistical Analysis, Time Series Analysis