Data Scientist - Clinical and Operational Analytics

Develop and deploy machine learning models to support clinical and operational decision-making. Work with large datasets to extract insights and support predictive analytics for human performance and health.

Requirements

Mandatory Qualifications:

•Bachelor's degree in a quantitative field (e.g., Computer Science, Applied Math).

•3+ years of experience in predictive analytics.

•Proficiency in Python, NumPy, Pandas, Matplotlib, and Scikit-learn.

•Ability to explain and implement ML algorithms from scratch.

•Signed NDA and HIPAA training required upon start.

Desired Qualifications:

•Experience with dashboard development and pretrained language models.

•Experience with dimensionality reduction and deep learning libraries (TensorFlow, PyTorch).

•Familiarity with human biology and performance.

Key Tasks and Responsibilities:

•Develop and tune unsupervised tree-based clustering models.

•Implement decision trees, k-NN, and optimized list sorting algorithms.

•Generate and minimize distance matrices using vectorized code.

•Collaborate with software engineers and maintain HIPAA compliance.