Wangboyan Zhang
actuarial consultant @ kpmg canada | actuarial science data analytics@ KPMG Canada
Waterloo, Ontario, Canada
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Wangboyan Zhang is an experienced professional with 8.4 years of work experience. He possesses strong communication and data analysis skills, along with proficiency in Microsoft Office and Excel. Based in Canada, Wangboyan has completed SOA/CAS Exam P/1 and FM/2 and has extensive working experience in actuarial science, financial mathematics, and data-oriented analytics. He is known for his problem-solving and analytical abilities, as well as his ability to multitask and work under tight deadlines. Wangboyan is proficient in MS Word, Excel, PowerPoint, Access, SQL, Matlab, and R, and has extensive workplace applications.
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Emails and Phone Numbers

@gmail.com
@kpmg.com
+1 855745****
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About

* Passed SOA/CAS Exam P/1 and FM/2; Sitting and actively preparing for STAM exam in February 2020 * Comprehensive working experience in actuarial science, financial mathematics, and data-oriented analytics * Strong problem-solving and analytical skills fostered through actuarial, data analytics and research experience * Proven ability to multi-task and work under tight deadlines; great contributor both individually and as a team player * Excellent communication and explanations skills honed from presenting reports and analytics to management at BMO * Proficient in MS Word, Excel, PowerPoint, Access, SQL, Matlab and R with extensive workplace applications

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Work Experience

333 Bay Street, Toronto, Ontario, M5H 2S5, CA

Financial Services

9340
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Wangboyan Zhang's Professional Milestones

  • Actuarial Student (2019-01-01~2019-04-01): Developed comprehensive actuarial models, providing valuable insights for decision-making and effective financial decision-making strategies.
  • Marketing Associate (2016-01-01~2016-04-01): Developed and executed successful marketing campaigns, driving brand awareness and increasing customer engagement.
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Education

University of Waterloo
University of Waterloo

Actuarial Science And Statistics

2014-2020