Data Scientist

Cape Fox is seeking a skilled Data Scientist with a strong background in unsupervised learning, predictive analytics, and algorithm development to support a government client. This role involves designing and deploying tree-based clustering models, implementing core algorithms such as decision trees and k-nearest neighbors from scratch, optimizing data structures like distance matrices, and writing efficient, vectorized Python code. The ideal candidate will hold a Bachelor’s degree in a quantitative field such as Computer Science, Applied Mathematics, or Economics, and have at least three years of hands-on experience in predictive analytics and Python development using libraries like NumPy, Pandas, Matplotlib, and Scikit-learn. Highly desirable qualifications include experience with AI/ML dashboard integration, dimensionality reduction, deep learning frameworks (TensorFlow, PyTorch), and familiarity with human biology, performance, and prior work with USAFSAM. This position is contingent upon contract award.

The salary range (or hiring range) for this exempt position has been established at: $96,000 – $120,000.

The above salary range represents the company’s good faith and reasonable estimate of the range of possible compensation at the time of posting. In addition, we offer a variety of benefits including company holidays, paid time off, health insurance, dental insurance, vision insurance, life and disability insurance, tuition reimbursement, as well as 401K with company matches. This job will be posted until filled or withdrawn.

Core Duties:

• Develop, deploy, and tune novel unsupervised tree-based clustering machine learning models
• Accurately describe how several classes of algorithms work and explain exactly how a decision tree works, and be able to code it from scratch
• Accurately explain the difference between density-based and binning-based clustering
• Accurately explain how the k-nearest neighbors algorithm works
• Implement the k-nearest neighbors’ algorithm, from scratch, in code (If unable to implement the naive version of the nearest neighbors, but not an optimized version, must be able to accurately describe an optimized version of k-nearest neighbors)
• Write an optimized list sorting algorithm, from scratch, in less than an hour, with no external resources
• Understand how to generate a distance matrix and demonstrate that they can minimize the size of a distance matrix in code
• Demonstrate writing vectorized code
• Obtain HIPAA training upon performance of work
• Maintain HIPPA standards and prevent data leaks

• Minimum of a Bachelor’s degree in an applied quantitative field (including Computer Science, Actuarial Science, Operations Research, Applied Mathematics, and Economics)
• At least three (3) years’ experience deploying predictive analytics
• Demonstrated experience with Python and object-oriented programming
• Demonstrated experience with standard data manipulation tools within Python, Numpy, Pandas etc.
• Demonstrated experience with standard plotting in Python, Matplotlib
• Demonstrated experience with Sci-Kit Lean and Pythons open-source machine learning software
• Highly Desired Qualifications
  • Experience working with software engineers to develop novel dashboards to enable interaction with AI technologies
  • Experience developing with pre-trained language models
  • Experience with Dimensionality reduction techniques
  • Experience with Tensorflow, Pytorch or other GPU enabled deep learning libraries
  • Experience working with USAFSAM
  • Prior study and familiarity with human biology
  • Prior study and familiarity with human performance
• Must be able to pass a Tier 1 Background Investigation
• Must have authorization to work in the United States as defined by the Immigration Reform Act of 1986