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# Senior Data Scientist - Life Sciences.AI

- **Company:** McKinsey & Co Inc
- **Location:** Philadelphia, PA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Amazon Web Services, Computer Vision, Microsoft Azure, Computer Programming, Data Warehousing, Github, Graph Database, Python (Programming Language), Machine Learning, NumPy, Cloud Services, Tensorflow, SQL Databases, Google Cloud, Graph Neural Networks, Pytorch, LangChain, Deep Learning, Keras, Pandas, Matplotlib, Containerization, Pyspark, Scikit Learn, Information Technology, Statistics Packages, Production Code, Dask, Software Version Control, Docker, Databricks
- **Published:** November 13, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-data-scientist-life-sciences-ai-philadelphia-pa--d5d12bdd-a980-4696-ae62-2cca559f55ac

## About the Role

Artificial Intelligence (AI), Data Science, Biology, Coaching, Mentoring, Diversity, Use Cases, Biology, Production Systems, Emerging Technology, * 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