Senior Data Scientist - Scientific AI

Your Impact

Your role will be split between developing new internal knowledge, building AI and machine learning models & pipelines, supporting client discussions, prototype development, and deploying directly with client delivery teams. You will bring distinctive statistical, machine learning, and AI competency to complex client problems.

You will help build and shape McKinsey’s scientific AI offering. You will play a pivotal role in the creation/dissemination of cutting-edge knowledge and proprietary assets. You will work in a multi-disciplinary team and build the firm’s reputation in your area of expertise.

You will ensure statistical validity and outputs of analytics, AI/ML models, and translate results for senior stakeholders. You will write optimized code to advance our Data Science Toolbox and codify analytical methodologies for future deployment.

You’ll be working in one of our offices in North America in our Life Sciences practice as a part of McKinsey’s global scientific AI team helping to answer industry questions related to how AI can be used for therapeutics, chemicals & materials (including small molecules, proteins, mRNA, polymers, etc.).

You will work with cutting edge AI teams on research and development topics in a start-up like environment, serving as a Senior Data Scientist in a technology development and delivery capacity.

You will support the manager of data science on the development of data science and analytics roadmap of assets across cell-level initiatives. You will deliver distinctive capabilities, models, and insights through your work with client teams and clients.

Your Qualifications and Skills

• Master’s degree with 5+ years or PhD degree with 2+ years of relevant experience in statistics, mathematics, computer science, or equivalent experience with experience in research
• Machine learning experience with causality, Bayesian statistics & optimization, survival analysis, design of experiments, longitudinal analysis, surrogate models, transformers, Knowledge Graphs, Agents, Graph NNs, Deep Learning, computer vision
• Strong programming experience in python (R, C++ optional) and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, stats models, pymc, pytorch/tf/keras, langchain)
• Proven experience applying machine learning techniques to solve business problems
• Experience with version control (GitHub)
• Proven track record of end-to-end ownership of independent workstreams
• Good presentation and communication skills (both verbal and written), with the ability to explain complex analytical concepts to people from other fields/non-technical stakeholders
• Proven experience advising external parties and/or functions
• Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment