I'm Yoonseul Choi, a data scientist with three years in healthcare analytics at HD Hyundai Medi Plus and an MS in Applied Statistics from Hanyang University. My work covers KPI design and Power BI dashboards on the industry side, and Bayesian hierarchical and spatial modelling on the research side.
My background is in statistics, with a graduate focus on spatial and Bayesian methods. After my BSc at Dongguk University, I joined HD Hyundai Medi Plus, the digital healthcare arm of HD Hyundai, where I spent three years on applied analytics across consumer, B2B, and clinical product lines.
The work split roughly into three areas. First, defining what an active member looks like for a digital health app and operationalising KPI metrics, retention, and churn through Power BI dashboards used in weekly executive review. Second, building an end-to-end healthcare cost prediction model on five years of Korea Health Panel data, using random effects regression layered with ensemble learning. Third, partnering with Kyobo Life Insurance on the clinical validation and B2B dashboarding for their Employee Assistance Program launch.
In parallel I'm finishing my MS in Applied Statistics at Hanyang University under Prof. Jungsoon Choi, with two arXiv preprints on spatial optimisation, a research internship at Academia Sinica on nonparametric bootstrapping for spatial point patterns, and a Workshop on Spatial Statistics 2025 talk.
I'm now looking for analyst, data scientist, or statistician roles in Australia. Open to most domains where rigorous quantitative work translates into real business or policy decisions.
Defined what counts as an "active member," built conversion funnels, and quantified retention, churn period, and carrying capacity for a digital health app, feeding a Power BI dashboard used in weekly executive review.
Five-year panel study on Korea Health Panel diabetes cohort. Random Effects Linear Regression on log-cost, four derived specifications compared, final 19-variable model validated on multicollinearity and autocorrelation. Productised as a member-facing lifestyle savings calculator.
Insight derivation for Kyobo Life Insurance's EAP launch. Ran user analysis and chronic-disease management effectiveness across treatment and comparison cohorts, then built B2B dashboards that became the foundation for the commercial pitch.
A two-stage hierarchical spatial framework identifying where surplus solar electricity in South Korea makes Bitcoin mining nationally profitable. Cost-benefit optimisation at the regional level, then geographic constraints applied at finer resolution. Three optimal regions identified, with combined potential of around USD 307M in annual net profit. Presented at WSS 2025; available on arXiv.
Under Prof. Junho Yang, working on nonparametric bootstrapping for spatial point patterns, focusing on inference for point processes with measurement error and computationally efficient methods for very large datasets. Concluded with a poster presentation.
Healthcare analytics across consumer, B2B, and clinical product lines. Owned the KPI committee, built the cost prediction model end-to-end, and partnered on the Kyobo EAP launch.
Investigated the representativeness of the National Fitness 100 dataset against the Korea National Health and Nutrition Examination Survey (KNHANES).
Multiple linear regression and Random Forest to identify promising handball players at an early stage. Handled data imbalance, KMO test, and Cronbach's alpha. Random Forest classifier reached F1 = 0.9936.
Under Prof. Jungsoon Choi (Spatial Statistics Lab). Coursework spans Bayesian Statistics, Spatial Statistics, Statistical Computing, Theory of Linear Models, Time Series, and Statistical Data Science.
Graduated in seven terms. Multiple academic excellence scholarships, plus tutoring assistant for Mathematical Statistics I. Member of the Big Data Society academic society 2019–2020.
Currently looking for analyst, data scientist, and statistician roles across Australia. Open to most domains where rigorous quantitative work translates into real business or policy decisions.