YOUR IMPACTYou will partner with global teams to create differentiated advanced analytics and agentic solutions that address high-value commercial use cases across the Life Sciences sector.
You will help transform standalone pilots into integrated, production-ready systems that reshape end-to-end commercial workflows and drive meaningful impact for patients.
You will leverage your advanced analytics expertise to solve complex problems, develop advanced machine learning models, design agentic flows, evaluate agentic outputs, write optimized code, and enhance our internal Data Science toolkit. You will collaborate on multiple projects, ensuring statistical rigor and reusable methodologies, while mentoring junior colleagues and supporting senior stakeholders in translating analytics into actionable insights. You'll explore emerging technologies and collaborate with diverse experts to deliver impactful innovations.
Your work will create real-world impact. By building cutting-edge technology assets, you will help clients modernize their commercial engagement model, harness the power of data, and achieve lasting improvements. Your contributions will enable organizations to unlock insights, get real-time insights from their data, and power our clients' future commercial capabilities.
You'll grow as a technologist and leader.You'll have the freedom to experiment with leading technologies, and work alongside inspiring, multidisciplinary teams. Your work offers a unique opportunity to innovate, learn, and make a tangible difference for clients worldwide.
You'll be working in one of our North American offices in our Life Sciences practice. You will help revolutionize how Pharma and MedTech companies connect with their customers to improve human lives. You will be working in a team that is fully integrated with QuantumBlack, AI by McKinsey.
There is flexibility to hire at the Senior Data Scientist I/II or Principal Data Scientist I/II level, depending on your experience.
YOUR QUALIFICATIONS AND SKILLS- Master's or PhD level in a discipline such as computer science, machine learning, applied statistics, mathematics, engineering, or artificial intelligence
- 5+ years of deep technical experience in machine learning, knowledge graphs, agents, evaluation frameworks for agentic outputs, graph neural networks, deep learning, computer vision, and statistics-related work
- Strong programming experience in Python and the relevant analytics libraries, such as pandas, NumPy, matplotlib, scikit-learn, statsmodels, PyMC, PyTorch/TensorFlow/Keras, LangChain, and LangGraph
- Ability to write production-grade code and experience with version control, such as GitHub
- While we advocate for using the right tech for the right task, we often leverage the following technologies: Python, PySpark, the PyData stack, SQL, Databricks, our own open-source data pipelining framework called Kedro, Dask/RAPIDS, container technologies such as Docker and Kubernetes, cloud solutions such as AWS, GCP, and Azure, and more
- Client-facing skills, e.g., working in close-knit teams on topics such as data warehousing and machine learning
- Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment
- Demonstrated leadership, either thought leadership or people leadership, e.g., managing project teams or direct reports
- Good presentation and communication skills, with a knack for explaining complex analytical concepts to people from other fields
- Willingness and ability to travel for work
- Strong communication skills, both verbal and written, in English, with the ability to adjust your style to suit different perspectives and seniority levels
Please review the additional requirements regarding essential job functions of McKinsey colleagues.
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