Joe Long

Joe Long

Senior Actuarial Data Scientist @ Milliman

About Joe Long

Joe Long is a Senior Actuarial Data Scientist at Milliman, where he has worked since 2013. He specializes in developing predictive modeling products and tools for health, life, and long-term care actuaries.

Work at Milliman

Joe Long has been employed at Milliman since 2013, serving as a Senior Actuarial Data Scientist. He is based in the Greater Minneapolis-St. Paul Area and focuses on actuarial data science applications. His role involves consulting on projects for insurers and other risk-taking entities, where he applies data science and machine learning techniques. Over his tenure, he has specialized in developing products and tools for health, life, and long-term care actuaries, utilizing predictive modeling to enhance decision-making processes.

Education and Expertise

Joe Long holds a Bachelor of Science degree in Mathematics and Statistics from North Dakota State University, where he studied from 2007 to 2011. He furthered his education at the same institution, earning a Master of Science in Applied Statistics from 2011 to 2013. His academic background provides a strong foundation for his expertise in actuarial data science, particularly in predictive modeling and its applications in the insurance industry.

Background

Before joining Milliman, Joe Long worked as a Graduate Assistant at North Dakota State University from 2011 to 2013. In this role, he gained valuable experience in research and academic support. Additionally, he completed a 10-month internship as an Automation Mathematician at Marvin in 2011, where he applied his mathematical skills in a practical setting. This combination of academic and professional experiences has shaped his career in actuarial science.

Professional Focus

In his current role, Joe Long specializes in developing innovative products and tools tailored for actuaries in health, life, and long-term care sectors. His work emphasizes the use of predictive modeling to improve actuarial practices. By integrating data science and machine learning techniques into consulting projects, he aims to provide actionable insights for insurers and other entities engaged in risk management.

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