Senior Fellow - Scientific AI
Your Impact
Your role will be split between supporting client service teams of scientific & technical colleagues, developing new internal knowledge & technology assets and building the firm’s external network.
You will bring distinctive medical knowledge to complex client Life Science R&D challenges through part-time staffing on client studies with a multi-disciplinary team.
You will drive proposal processes and participate in client negotiations by identifying end-to-end opportunities to transform Life Sciences R&D and architecting solutions that address specific client needs. You will also advance the latest thinking in scientific AI and generate a steady stream of whitepapers, scientific publications and keynote speeches in top scientific and AI conferences and journals.
Your role will also include establishing an external network & playing a lead role in external reputation building and attracting and retaining junior colleagues by mentoring them to expand their scientific AI knowledge and impact. You will lead firm and cell-level initiatives to scale our service in scientific AI and continuously improve the productivity & impact of our service line.
You will work as a member of McKinsey’s global scientific AI team to transform the way our clients do research and development in industries where scientific innovation is core to value creation. With your specific expertise at the intersection of medical science and artificial intelligence / machine learning (i.e., deep learning, causal inference, Bayesian modelling, and foundation models), you will help build and lead McKinsey’s forward-looking capabilities to transform clients’ innovation engines.
Your core responsibilities will entail the following: 1) Delivery of distinctive capabilities, knowledge, and insights through your work with client service teams and clients; 2) Technical and scientific leadership in the creation & dissemination of cutting-edge knowledge and proprietary assets; and 3) Elevation of the firm’s reputation in your area of medical expertise.
Your qualifications and skills
- Must possess a medical degree (MD) and have successfully completed a residency program
- Proven mastery of fundamental concepts in one or multiple branches of a specific medical science (e.g., immunology, oncology, metabolic disease, neuroscience) as well as being up-to-date on latest ideas and publications
- Deep understanding of the data sources, AI methods and related analytical technologies, e.g., AI principles, deep learning, machine learning (supervised learning or unsupervised), causal inference, large language models, foundation models, computer vision, diffusion models, reinforcement learning, knowledge graphs, or computer vision
- Ability to develop new-to-world solution architecture blueprints, and decompose the end-state solution into incremental releases to prove feasibility and deliver value
- Track record of innovation at the intersection of AI and medicine
- Track record of recent leadership and engagement in the external ecosystem via publications, conference participation, keynote speeches, connectedness with academia and/or industry
- Experience managing direct reports, or a complex network of internal & external stakeholders
- Compelling communicator with track record of translating technical methods to non-technical executive stakeholders as well as counselling non-technical stakeholders on the opportunity, the specific solution, and the technical and organizational requirements required for sustainable change and value capture
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