Major accountabilities:

• Domain Expertise:
  • Possess a knowledge across the end-to-end pharmaceutical value chain, including drug discovery, preclinical and clinical trials, regulatory affairs, pharmacovigilance, technical operations (manufacturing, supply chain, and quality assurance), and commercial operations (market access, sales, and marketing), to lead AI-driven initiatives.
  • Stay updated on advancements in Generative AI and their applications to optimize processes across the pharmaceutical value chain, from R&D to commercialization.
• Business Analysis:
  • Partner with senior stakeholders across R&D, manufacturing, and commercial teams to gather, document, and analyse complex business requirements, ensuring alignment with strategic organizational goals.
  • Conduct in-depth analyses of business processes across the E2E value chain, identifying opportunities for Generative AI to enhance efficiency, quality, and market competitiveness.
  • Develop detailed business cases, feasibility studies, and cost-benefit analyses to prioritize AI initiatives in drug development, manufacturing optimization, and commercial strategies.
  • Create comprehensive business requirements documents, process flow diagrams, and solution blueprints to guide AI implementation across the value chain.
• Stakeholder Engagement:
  • Translate complex AI concepts into actionable insights for technical and non-technical stakeholders in R&D, technical operations, and commercial teams, securing buy-in and alignment.
  • Facilitate workshops, strategy sessions, and cross-functional meetings to drive consensus on AI projects spanning discovery to commercialization.
  • Mentor junior analysts to build team capability in AI-driven business analysis within the pharmaceutical value chain.
• Generative AI:
  • Leverage Generative AI to analyse large, complex datasets across the value chain, uncovering patterns, trends, and insights for applications like drug candidate identification, manufacturing process optimization, and market demand forecasting.
  • Collaborate with data scientists and AI engineers to design, develop, and deploy AI models tailored to specific needs in R&D, manufacturing, and commercial operations.
  • Ensure AI solutions are interpretable, scalable, and integrated into workflows across the E2E value chain, from lab to market.
• Regulatory & Ethical Compliance:
  • Ensure AI solutions comply with global regulatory requirements (e.g., USFDA, EU, PMDA) and ethical standards across all stages of the pharmaceutical value chain, including manufacturing and commercial activities.
  • Identify and mitigate risks related to AI deployment, such as data privacy, model bias, and compliance with Good Manufacturing Practices (GMP).

Minimum Requirements:

• Possess 6–8 years of core Business Analyst experience in the life sciences domain, with at least 3 years focused on AI technologies across the pharmaceutical value chain (R&D, manufacturing, and commercial operations), complemented by a master’s degree in Life Sciences, Biomedical Sciences, Computer Science, Data Science, or a related field. A PhD is a plus.
• Strong understanding of Generative AI, machine learning, and their applications in drug discovery, clinical trials, manufacturing, and commercial strategies. Proficiency in data analysis and visualization tools (e.g., Python, R, Tableau) to interpret complex datasets.
• Proven project management skills, with a track record of leading AI-related projects in at least one segment of the pharmaceutical value chain.
• Strong analytical and problem-solving abilities, with a strategic mindset and attention to detail.
• Exceptional communication and interpersonal skills, with the ability to mentor teams and influence stakeholders across R&D, technical operations, and commercial functions.
• Familiarity with pharmaceutical regulatory requirements (e.g., FDA, EMA, PMDA) and industry standards, including GMP and commercial compliance.

Why consider Novartis?

Our purpose is to reimagine medicine to improve and extend people’s lives and our vision is to become the most valued and trusted medicines company in the world. How can we achieve this? With our people. It is our associates that drive us each day to reach our ambitions. Be a part of this mission and join us!
Learn more here:

http://www.novartis.com/about/strategy/people-and-culture

Commitment to Diversity and Inclusion:
Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.
Join our Novartis Network: If this role is not suitable to your experience or career goals but you wish to stay connected to hear more about Novartis and our career opportunities, join the Novartis Network here:
http://talentnetwork.novartis.com/network