Joe Long is a consulting actuary and data scientist with the Minneapolis office of Milliman. He joined the firm in 2013.
Joe specializes in the application of data science and machine learning within the actuarial setting, with an emphasis on health and long-term care. In addition to his consulting work for insurers and other risk-taking entities, this work includes assisting health, life, and long-term care actuaries in developing products and tools that utilize predictive modeling.
Joe leads the development of machine learning models that are included in the Milliman Advanced Risk Adjusters™ (MARA™) and Milliman Long-term Care Advanced Analytics™ (LARA™) software products. Joe routinely uses cloud computing resources to speed up computationally intensive modeling tasks.
More recently, Joe has been focused on developing custom MARA models for clients in other countries, including China and the Middle East, and for new populations in the United States. Recently, he developed a suite of custom models that were adopted by the State of Utah for Medicaid capitation rate setting.
A frequent speaker at industry meetings on machine learning topics, Joe is also experienced in communicating technical modeling concepts in plain language that non-experts can understand. He actively pursues ways to open the “black box” of advanced models so that the key drivers of predictions can be understood and validated by all stakeholders.
Nielmberg, Michael, Joe Long, Stephen Charlesworth, and Meseret Woldeyes. "Consumer data and its applications in health insurance underwriting." Milliman. May 2023.
Anderson, Jeff, Robert Eaton, Missy Gordon, Yang Jing, Joe Long, and Juliet Spector. "Superior predictive performance of Milliman LARA models." Long-Term Care News. March 1, 2023.
Eaton, Robert, Juliet Spector, Jeff Anderson, Joe Long, Brian Hartman, and Missy Gordon. "Evaluating LTC population health programs." Long-Term Care News. February 16, 2023.
Gaweda, Bartosz, Christoph Krischanitz, Rémi Bellina, Jeff Anderson, Joe Long, Noriyuki Kogo, Saiki Makino, and Scott Chow. "Potential data sources for life insurance AI modelling." Milliman. April 22, 2022.
Eaton, Robert, Missy Gordon, Jeff Anderson, Juliet Spector, and Joe Long. "Long-term care wellness initiatives: A simulated pilot program." Milliman. December 1, 2021.
Beach, Van, Jonathan Glowacki, Makho Mashoba, Benjamin Buttin, Alexandre Boumezoued, Joe Long, Zohair Motiwalla, Josh Dobiac, Antoine Ly, and David South. "Cloud computing and machine learning uses in the actuarial profession." Society of Actuaries. April 5, 2021.
Bergerson, Mike, Missy Gordon, John Hebig, and Joe Long. "Unpacking predictive analytics for the long-term care insurance industry." Society of Actuaries. March 22, 2021.
Gordon, Missy, and Joe Long. "Case study part 3: Improving financial projections for long-term care insurance with predictive analytics." Long-Term Care News. August 17, 2018.
Long, Joe, and Dan McCurley. "Parallel cloud computing: Making massive actuarial risk analysis possible." Society of Actuaries. May 2, 2018.
Gordon, Missy & Joe Long. "Case study, part 2: Improving financial projections for long-term care insurance with predictive analytics." Long-Term Care News. April 25, 2018.
Gordon, Missy & Joe Long. "Case study, part 1: Improving financial projections for long-term care insurance with predictive analytics." Long-Term Care News. January 12, 2018.
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