Data Scientist & Educational Researcher with Biostatistics Expertise

Chong Li ***********@*****.*** · +1-681-***-****

· LinkedIn: https://www.linkedin.com/in/chong-li-83b019247/ Qualification

• Data Scientist Ph.D. in Mathematics

Specialized in statistical modeling, machine learning, and data visualization, with deep expertise in trans- forming complex datasets into clear, meaningful analyses.

• Over 5 years of experience analyzing complex datasets, developing regression models, and delivering actionable insights across healthcare, education, and research. Education

• West Virginia University. (GPA:3.75/4.0) Morgantown, WV Ph.D. in Mathematics 08/2018 - 12/2023

Relevant coursework: Analysis of Time-to-Event Data; Statistics in Clinical Trials. My research centers on graph theory problem-solving and biostatistics projects, with emphasis on data cleaning, data analysis, and statistical consulting, and apply the results to real world educational and health issues.

• Northwestern Polytechnical University. Xi’an, China M.S. in Applied Mathematics 08/2015 - 03/2018

Relevant coursework: Advanced Stochastic Process, Advanced Statistics, Multivariate Statistical Analysis, Algorithms Analysis and Design

• Shandong University of Science and Technology Qingdao, China B.S. in Information and Computing Science 08/2010 - 06/2014 Work & Project Experience

• Southern Arkansas University Magnolia, AR

Assistant Professor in Mathematics and Computer Science 08/2023-current

– Organized and led math contest preparation sessions, mentoring students in analytical problem-solving and enhancing overall team performance. 2024

– Built a web-scraping workflow to collect and preprocess vaccine news data and applied prompt engineering techniques to steer LLMs toward concise, domain-specific summaries. 2024

– Identified top drivers to arthritis pain severity by building linear mixed models, which helped to suggest beneficial activities like yoga to patients, reducing follow-up visit frequency by 3.4%. 2023- 2025

submitted to the American College of Rheumatology conference, Washington DC, Nov 14-19, 2024

– Evaluated how the adoption of 3D-printed brain models impact student course performance using linear regression, demonstrating their positive influence on student achievement. 2023-2024

• West Virginia University Morgantown,WV

Research assistant in Department of Biostatistics 08/2021-05/2023

– Analyzed keyword frequency differences between two social-media user cohorts using chi-square tests and visualized results with Tableau bar and scatter plots to uncover healthcare-related preferences, enabling more targeted content recommendations. 2021

– Performed a meta-analysis of interpersonal psychotherapy (IPT) efficacy in China, showing up to

10 greater clinical improvement vs. standard treatment and highlighting therapist supervision gaps

( 25% reporting), informing policy recommendations for training and implementation scalability. 2023

Published in Frontiers in Psychiatry, section PublicMentalHealth,2023, 14, DOI 10.3389/fpsyt.2023.1160081

– Developed a diagnosis-time LightGBM survival model (c-index 0.68) that separated patients into three clinically distinct survival risk tiers (median overall survival: 20 vs. 12 vs. 7 months), improving early treatment pathway selection. 2023

Technical skills

• Programming: Python, SQL, R

• Analytics & Machine Learning: Power BI, Tableau, supervised and unsupervised ML, AB test, LLM

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