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:
- Bayesian Statistics
- R
- Python
- Machine Learning
- Time Series
- Financial Mathematics
- Quantitative Risk
- Probability Theory
- Non-Parametric Statistics
Regan Russell's Problem Solving Experience:
- 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.
- Built a model to predict customer churn using telecommunications customer data. Achieved 82% prediction accuracy and identified 3 significant variables to improve churn rate.
- Compressed a data set containing 1 million, 7 year yield curve scenarios into 1 million, 1 point data set using principal component analysis.