Data Scientist – Scientific AI – Life Sciences
| Company | McKinsey & Company |
|---|---|
| Location | Boston, MA, USA, Seattle, WA, USA, Houston, TX, USA, Washington, DC, USA, San Francisco, CA, USA, Austin, TX, USA, Los Angeles, CA, USA, Jackson Township, NJ, USA, Philadelphia, PA, USA, Chicago, IL, USA, Charlotte, NC, USA, Pittsburgh, PA, USA, New York, NY, USA, Mountain View, CA, USA, Atlanta, GA, USA, Darien, CT, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Master’s, PhD |
| Experience Level | Mid Level |
Requirements
- Master’s or PhD degree with 2+ years of relevant experience in statistics, mathematics, computer science, or equivalent experience with experience in research
- Proven experience applying machine learning techniques to solve business problems
- Proven experience in translating technical methods to non-technical stakeholders
- 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, Knowledge Graphs, Agents, Graph NNs, Deep Learning, computer vision
- Ability to write production code and object-oriented programming
Responsibilities
- Develop new internal knowledge
- Build AI and machine learning models & pipelines
- Support client discussions
- Prototype development
- Deploy directly with client delivery teams
- Ensure statistical validity and outputs of analytics, AI/ML models and translate results for senior stakeholders
- Write optimized code to advance our Data Science Toolbox and codify analytical methodologies for future deployment
Preferred Qualifications
-
No preferred qualifications provided.