MINQI (BRUCE) ZHANG
Waterloo,ON
Summary
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.
Overview
3
3
years of professional experience
Work History
Actuarial Analyst (National PI Property Pricing)
Definity Insurance
2023.01 - Current
- Improved alignment on pricing models across regions by designing new modelling framework in Radar to be used countrywide for Homeowner products
- Performed top-line and bottom-line analysis on property products across nation. Communicated key results to stakeholders and provided solutions through rate changes
- Collaborated with other functions (Business platform, Product, UW, Portfolio management) to conduct non-pricing changes and profile testings on ratebooks to ensure legal compliance and fulfill business goals
Actuarial Analyst Intern (Alberta PI Pricing)
Definity Insurance
2022.01 - 2022.08
- Supported multiple rate changes analysis and fillings for both PPV and property lines in Alberta
- Improved forecasting accuracy of homeowner product QtB by developing XGBoost closing model with AUC of 0.83
- Maintained and monitored monthly loss ratio and GWP reports and provide necessary analysis on unusual KPIs
Actuarial Intern (Economic Capital)
Aviva Canada
2021.01 - 2021.04
- Established new statistical model for company-wide Loss Ratios with Bayesian method in R for Tier II Capital Allocation
- Participated in monthly department meeting as secretary by preparing agenda and writing minutes
- Conducted Ad hoc data analysis for multiple projects
Education
Bachelor of Mathematics - Actuarial Science & Statistics
University of Waterloo
Waterloo, ON06.2023
Skills
- Exam P
- Exam FM
- Exam IFM
- Exam MAS1
- Exam MAS2
- Exam 5 (Sitting in Spring 2024)
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.
Timeline
Actuarial Analyst (National PI Property Pricing)
Definity Insurance
2023.01 - Current
Actuarial Analyst Intern (Alberta PI Pricing)
Definity Insurance
2022.01 - 2022.08
Actuarial Intern (Economic Capital)
Aviva Canada
2021.01 - 2021.04
Bachelor of Mathematics - Actuarial Science & Statistics
University of Waterloo
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