Life Insurance Office Staff

CARL GUO

waterloo, on • 647-***-**** • adihd9@r.postjobfree.com

Actuarial Analyst Intern

Currently pursuing a Bachelor’s degree at the University of Waterloo in Actuarial Science and Statistics

Proficient knowledge of Word, Excel, PowerPoint, and Access; programming skills (Visual Basic, R, Python, etc.) and visualization tools like Tableau and SAS

Knowledge of pricing, reserving, capital management or analytics; ability to work within a team structure and deliver high-quality work under time constraints

Able to support practice leaders by delivering work on a wide range of consulting projects within actuarial, underwriting / claims and advanced analytics domains

Trained to support actuarial audit engagements, with the objective of introducing new technologies such as Robotics Process Automation (RPA) to drive efficiency

Strong commitment to personal learning and development; understands expectations and demonstrates personal accountability for keeping performance on-track

Actively focuses on developing effective communication and relationship-building skills; understands how daily work contributes to the priorities of the team

Education / Training

Bachelor’s Degree - Actuarial Science Major & Statistics, University of Waterloo, Waterloo, ON

Expected Dec 2020

Achieved Dean’s Honours and Distinction, 2020

Recipient of President Scholarship, 2017

Society of Actuaries: Preliminary Exams: P, FM, IFM, SRM, VEE Mathematical Statistics, VEE Accounting and Finance, VEE Economics

SAS 9 Certified Base Programmer

SAS 9 Certified Advanced Programmer

Professional Experience

SALES ASSISTANT MAY 2019 - AUGUST 2019

American International Assurance Co. Ltd. Beijing, China

Solicited new business outside of the office, at business establishments and other locations to create and expand business networks.

Built rapport critical to establishing client satisfaction and quickly processed calculations of premiums for health and life insurance,

Generated sales, retained existing members, and grew book of business through multiple product offerings.

Responded to customer inquiries and requests relating to insurance, membership, and financial products.

Partner with sales manager and other office staff, in cross-selling insurance products,

Identified opportunities and facilitated basic improvements to processes and systems

Performed routine tasks under direct supervision and within established procedures and guidelines

Liaised between IT and Actuarial department, ensuring requests were received and fulfilled

Analyzed and summarized insurance products, strategizing the launch of new products suited to diverse customer needs

Researched competitors and their products; compiled a comparison summary of life insurance products outlining product pros and cons

Academic Projects

Stat Learning-Classification Course (in progress)

Google’s 2020 landmark recognition in Kaggle challenge is an important application for our image classification.

This project will process huge image data to classify different landmarks. Among them, we applied the convolutional neural network (CNN) method to classify images. And learn the training data.

Then check the model and apply it to the test set. The challenges and difficulties involved are huge. I had to learn a lot of programming languages because of many python programs, and the amount of data to be processed for this challenge is huge.

Life Contingencies Course

Use Excel to make a life table, use Excel function to calculate survival probability and actuarial data of Markham mortality model, and use Excel to apply mortality improvement model on different data.

Calculate mortgage and insurance premiums.

Use random numbers to simulate many Insurance portfolios and calculate the loss variance and expected value. Extensive use of Excel

Applied Linear Models Course

Explore the relation healthy male single-fetus birth weight and some explanatory variables using the given data set of the information of the baby boy and his mother.

Use R to select the variables of the linear model of the data. Validate and filter the model matching degree and calculate the confidence interval and related data.

Finally write the project report. The challenge and difficulty lie in the need to write a lot of programs in R and how to use the program to select appropriate variables.

How to perform model selection. Since R language is a self-study content in university courses, my team members and I spent a lot of time learning the writing and application of R language.

Computational Inference Course

Use Bayesian method to classify the data hierarchically, write Gibbs sampler in R and use Gibbs sampler to sample the provided data and verify its accuracy, and finally write a project report.

The challenge and difficulty are that this course will lead the programming difficulty of R language reaching new heights is a very difficult task for non-CS majors.

The team members and I put in a lot of learning and practice to compile the Gibbs sampler. It took a long time to learn according to the examples provided by the professor and apply it to our own project.

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