Problem Solver

Regan Russell

Regan Russell

Areas Regan Russell is Knowledgeable in:

Statistics, Machine Learning, Actuarial Science

Techniques Regan Russell Uses:

Principal Component Analysis, Machine Learning, Natural Language Processing, Statistics

Regan Russell's Problem Solving Skills:

  1. Bayesian Statistics
  2. R
  3. Python
  4. Machine Learning
  5. Time Series
  6. Financial Mathematics
  7. Quantitative Risk
  8. Probability Theory
  9. Non-Parametric Statistics

Regan Russell's Problem Solving Experience:

  1. Built a natural language processing model to predict customer satisfaction using airline customer review data. Achieved 81% prediction accuracy and identified multiple significant causes for customer dissatisfaction.
  2. Built a model to predict customer churn using telecommunications customer data. Achieved 82% prediction accuracy and identified 3 significant variables to improve churn rate.
  3. Compressed a data set containing 1 million, 7 year yield curve scenarios into 1 million, 1 point data set using principal component analysis.