Your Growth You will be working in our London officein our Life Sciences practice. You will work with cutting edge AIteams on research and development topics across our life sciences,global energy and materials (GEM), and advanced industries (AI)practices, serving as a Senior Data Scientist in a technologydevelopment and delivery capacity. You will be on McKinsey’s globalscientific AI team helping to answer industry questions related tohow AI can be used for therapeutics, chemicals & materials(including small molecules, proteins, mRNA, polymers, etc.). Inthis role you will support the manager of data science on thedevelopment of data science and analytics roadmap of assets acrosscell-level initiatives. You will deliver distinctive capabilities,models, and insights through your work with client teams andclients. Your Impact Your role will be split between developing newinternal knowledge, building AI and machine learning models &pipelines, supporting client discussions, prototype development,and deploying directly with client delivery teams. You will bringdistinctive statistical, machine learning, and AI competency tocomplex client problems. With your expertise in advancedmathematics, statistics, and/or machine learning, you will helpbuild and shape McKinsey’s scientific AI offering. As a Senior DataScientist, you will play a pivotal role in thecreation/dissemination of cutting-edge knowledge and proprietaryassets. You will work in a multi-disciplinary team and build thefirm’s reputation in your area of expertise. You will ensurestatistical validity and outputs of analytics, AI/ML models andtranslate results for senior stakeholders. You will write optimizedcode to advance our Data Science Toolbox and codify analyticalmethodologies for future deployment. Your qualifications and skills- Master’s degree with 5+ years or PhD degree with 2+ years ofrelevant experience in statistics, mathematics, computer science,or equivalent experience with experience in research - Experiencein client delivery with direct client contact - Proven experienceapplying machine learning techniques to solve business problems -Proven experience in translating technical methods to non-technicalstakeholders - Strong programming experience in python (R, Python,C++ optional) and the relevant analytics libraries (e.g., pandas,numpy, matplotlib, scikit-learn, statsmodels, pymc,pytorch/tf/keras, langchain) - Experience with version control(GitHub) - ML experience with causality, Bayesian statistics &optimization, survival analysis, design of experiments,longitudinal analysis, surrogate models, transformers, KnowledgeGraphs, Agents, Graph NNs, Deep Learning, computer vision - Abilityto write production code and object-oriented programming#J-18808-Ljbffr
