Performance-driven Actuarial Analyst with solid knowledge and experience in P&C insurance pricing. Excellent analytical skills in data visualization, predictive modelling and statistical learning with advanced grasp of Python, SQL and R. Works with little to no supervision and also collaborative in team projects.
Driver Risk Identification(ACTSC 489 - Application of Machine Learning in Insurance)
Worked with real-world insurance data set to predict the safeness of drivers. Utilized supervised (XGboost, Random Forest, GLM) and unsupervised learning (K-Means) techniques to build predictive models. Presented and explained technical results to the fellow students and industrial experts.