Justin Chow, Fsa

Justin Chow, Fsa

Actuary @ Milliman

About Justin Chow, Fsa

Justin Chow is an actuary with extensive experience in valuation processes for life insurance and deferred annuities. He currently works at Milliman, where he manages a team of actuarial analysts and has contributed insights on Medicaid financial metrics.

Work at Milliman

Currently, Justin Chow serves as an Actuary at Milliman, a position he has held since 2019 in the Indianapolis, Indiana Area. His role involves managing a team of actuarial analysts and working extensively with SAS Statistical Software. He focuses on state Medicaid programs and various commercial health research projects. Previously, he worked as an Associate Actuary at Milliman from 2013 to 2019, contributing to various actuarial processes and projects.

Education and Expertise

Justin Chow earned a Bachelor of Science in Business Administration with a focus on Actuarial Science and Information Systems from Drake University, studying from 2010 to 2013. He also attended INTI College Subang Jaya from 2008 to 2009. He is proficient in Visual Basic, SQL, and EXL LifePro systems, and is familiar with Pragmatic Programmer concepts and QlikView business intelligence software.

Background in Actuarial Science

Justin Chow has a background in valuation processes for life insurance and deferred annuities, utilizing AXXX and AG33 guidelines. His experience includes an internship at EMC National Life in 2012, where he worked as an Actuarial Intern for 10 months in the Des Moines, Iowa Area. This foundational experience contributed to his career development in the actuarial field.

Achievements in Data Automation and Insights

Justin has developed client-facing dashboards known as DRIVE, which provide insights for clients. He has experience in establishing project workflow and data automation. Additionally, he shared insights on the impact of COVID-19 on Medicaid financial metrics through a presentation during the annual firm-wide forum, showcasing his ability to communicate complex data effectively.

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