Talex Diede
Talex Diede is an actuarial data scientist with the Life Practice in Milliman's Seattle office. She works primarily with the life and annuity predictive analytics group. She joined the firm in 2013.
Experience
Since joining Milliman, Talex has primarily worked on predictive modeling, with a focus on policyholder behavior. She specializes in data analysis and data manipulation in addition to statistical modeling and manages projects related to predictive modeling. She has experience with traditional statistical model building methods and machine learning methods. Recent projects include investigating uses of big data to improve predictions of policyholder behavior. She has strong technical skills, which make her well suited to predictive modeling projects and others. She is also a frequent presenter on topics related to predictive modeling. Other projects she has worked on include, but are not limited to, model validation, product design, and assumption review.
- “Bull’s-eye! Using targeted products and market segmentation in life insurance to benefit both insurer and customer.” The Actuary magazine, June/July 2018.
- “Predictive Analytics Applications,” 2018 Valuation Actuary Symposium.
- “Customer Segmentation and Profitability Analysis,” 2018 Predictive Analytics Symposium.
- “Machine Learning Topics,” 2017 & 2018 Practical Predictive Analytics Seminar.
- “Using Predictive Analytics to Set Actuarial Assumptions,” 2016 Valuation Actuary Symposium.
- “Lapse Tail Risk: An application of predictive modeling in economic capital calculation,” Milliman research report.
- “Variable Annuity Lapse and Utilization Experience Studies,” Milliman report.
- Associate, Society of Actuaries
- Member, American Academy of Actuaries
- MSc, Computational Finance and Risk Management, University of Washington
- BS, Applied and Computational Mathematical Sciences and Economics, University of Washington