Senior Fellow - Scientific AI (Clinical Biostatistician)
McKinsey & Company · Amsterdam +33 · 4d ago
Staff / Lead / PrincipalOn-siteMachine Learning & AI
Who you'll work with
Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.
In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else.
When you join us, you will have:
- Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
- A voice that matters: From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
- Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
- World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.
What you'll do
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.
You will help build and lead McKinsey's forward-looking capabilities to transform clients' innovation engines.
With your specific expertise at the intersection of clinical biostatistics and artificial intelligence / machine learning (i.e., deep learning, causal inference, Bayesian modelling, and foundation models), you will bring distinctive statistical knowledge to complex client Life Sciences 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 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.
You will also establish an external network, play a lead role in external reputation building, and attract and retain junior colleagues by mentoring them to expand their scientific AI knowledge and impact.
Your background
- Must possess an advanced degree – PhD in Biostatistics, Statistics, or a closely related quantitative discipline (or an MD with strong biostatistical training)
- Proven mastery of fundamental concepts in clinical biostatistics, as well as being up-to-date on latest ideas and publications, including: Deep understanding of developing statistical analysis plans (SAPs) in pharma; Experience of clinical trial simulation; Adaptive clinical trials; Bayesian network meta-analysis; Platform clinical trials
- Deep understanding of the data sources, AI methods and related analytical technologies, e.g., AI principles, deep learning, machine learning (supervised or unsupervised), causal inference, large language models, foundation models, diffusion models, reinforcement learning, and knowledge graphs
- 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 clinical trial design / biostatistics
- Track record of recent leadership and engagement in the external ecosystem via publications, conference participation, keynote speeches, and 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