Xiaomeng Zhao is a data scientist-in-training and pragmatic analyst with seven years of experience building automated ETL pipelines, ML models, and analytics dashboards across healthcare, finance, and agriculture. Currently pursuing an MDSAI at the University of Waterloo and working as a Data Analyst Co-op, she standardized 300+ public scRNA-seq datasets, automated literature and GEO retrieval systems, and developed ML-driven biomarker discovery workflows in Linux/PyTorch environments. Her background spans production-ready engineering (Bash, SQL, cloud) and applied modeling (LASSO, Elastic Net, RSF) with measurable impacts like 70% automated Seurat builds and substantial reductions in manual workload. Comfortable moving between research and regulated settings, she has improved credit and PD/LGD estimations, enhanced volatility modeling, and created interactive dashboards for operational decision-making. Xiaomeng is seeking roles starting Jan 2026 that leverage her cross-domain blend of data engineering, survival analysis, and reproducible research practices.
7 years of coding experience
Bachelor of Science - BS Statistics, Bachelor of Science - BS Statistics at Queen's University
Soochow University (CN)
Master's degree Data Science and Artificial Intellegence, Master's degree Data Science and Artificial Intellegence at University of Waterloo
Contributions:4 PRs, 702 pushes, 72 branches in 11 months
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