Data Scientist - Clinical and Operational Analytics

Description:

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.