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For Companies At a Glance
- Tasks: Join McKinsey's scientific AI team to revolutionize R&D in key industries.
- Company: Be part of a global leader in consulting, driving innovation and scientific advancement.
- Benefits: Enjoy opportunities for mentorship, networking, and contributing to impactful projects.
- Why this job: Shape the future of scientific AI while collaborating with top experts and clients.
- Qualifications: Mastery in science and AI methods; strong communication and leadership skills required.
- Other info: Engage in high-profile conferences and publications to elevate your professional profile.
The predicted salary is between 72000 - 108000 £ per year.
Your Growth
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: Life Sciences, Specialty Chemicals, Global Energy and Materials, Agriculture, Advanced Industries, and Sustainability. With your expertise at the intersection of a core scientific discipline or disciplines (i.e., chemistry, medicine, computational biology, protein engineering, materials, biostatistics, physics) 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:
- Delivery of distinctive capabilities, knowledge, and insights through your work with client service teams and clients
- Technical and scientific leadership in the creation & dissemination of cutting-edge knowledge and proprietary assets
- Elevation of the firm\’s reputation in your area of expertise
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 be expected to bring distinctive knowledge to complex client/CST problems 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 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.
Your qualifications and skills
- Proven mastery of fundamental concepts in one or multiple branches of a specific science (chemistry, medicine, computational biology, protein engineering, materials, biostatistics, physics) 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 based on industry/client needs, 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 a scientific discipline
- 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
- 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
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Senior Knowledge Expert, Scientific AI employer: McKinsey & Company
Contact Detail:
McKinsey & Company Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Knowledge Expert, Scientific AI
✨Tip Number 1
Make sure to showcase your expertise in both a specific scientific discipline and AI methods. Highlight any innovative projects you've worked on that demonstrate your ability to merge these fields, as this is crucial for the role.
✨Tip Number 2
Network actively within the scientific and AI communities. Attend conferences, engage in discussions, and connect with thought leaders. This will not only enhance your knowledge but also help you build relationships that could be beneficial for your application.
✨Tip Number 3
Prepare to discuss your experience in mentoring and leading teams. Be ready to share examples of how you've helped junior colleagues grow their skills, as this aligns with the firm's focus on attracting and retaining talent.
✨Tip Number 4
Stay updated on the latest trends and publications in scientific AI. Being able to reference recent advancements or case studies during your conversations can set you apart and demonstrate your commitment to the field.
We think you need these skills to ace Senior Knowledge Expert, Scientific AI
Some tips for your application 🫡
Highlight Your Expertise: Make sure to clearly showcase your mastery in one or multiple scientific disciplines relevant to the role, such as chemistry, medicine, or computational biology. Provide specific examples of how you've applied this knowledge in previous roles.
Demonstrate AI Knowledge: Emphasize your understanding of AI methods and technologies. Include details about your experience with deep learning, machine learning, and other relevant analytical technologies. Use concrete examples to illustrate your capabilities.
Showcase Communication Skills: Since the role requires translating complex technical concepts to non-technical stakeholders, include examples of how you've successfully communicated intricate ideas in past experiences. Highlight any presentations or publications you've contributed to.
Detail Leadership Experience: Mention your experience in managing teams or engaging with external stakeholders. Provide examples of how you've led initiatives or mentored junior colleagues, showcasing your ability to build networks and enhance the firm's reputation.
How to prepare for a job interview at McKinsey & Company
✨Showcase Your Scientific Expertise
Be prepared to discuss your mastery in specific scientific disciplines. Highlight your knowledge of recent publications and innovations in fields like chemistry, medicine, or computational biology, as this will demonstrate your up-to-date understanding and relevance in the industry.
✨Demonstrate AI Proficiency
Make sure to articulate your experience with various AI methods and technologies. Be ready to provide examples of how you've applied deep learning, machine learning, or causal inference in real-world scenarios, showcasing your ability to bridge science and AI effectively.
✨Communicate Effectively with Non-Technical Stakeholders
Prepare to explain complex technical concepts in a way that is accessible to non-technical audiences. Practice translating your scientific and AI knowledge into actionable insights that can drive decision-making for executive stakeholders.
✨Highlight Leadership and Mentorship Experience
Discuss your experience in leading teams and mentoring junior colleagues. Share specific examples of how you've contributed to building a strong external network and enhancing the reputation of your previous organizations in the scientific AI community.
