I'm a Data Scientist with 5+ years of Research and Professional experience in Statistics, Machine Learning, and Experimentation & Causal Inference. Areas of Expertise include: 1. A/B Tests, aka Randomized Controlled Trials - Power Analysis (Sample Size Calculation), Variance Reduction (e.g., Stratification, Post-Stratification, CUPED), Data Workflow, Missing Data, Interleaving, Metrics, Measurement Validity, Sampling, and Resampling (Bootstrap and Permutation). 2. Quasi-Experimental Methods - Difference-In-Differences, Regression Discontinuity Design, Comparative Interrupted Time-Series, Instrumental Variables, Panel Design, Switchback, and Synthetic Control 3. Observational Methods - Matching, Propensity Score Matching, Propensity Score Stratification, Inverse Probability Treatment Weighting (IPTW), and Covariate Adjustment 4. Machine Learning - Supervised: Linear/Logistic Regressions, Decision Tree, Random Forest, K-Nearest Neighbors, Support Vector Machines, XGBoosting, etc. - Unsupervised: Clustering (K-Means, Hierarchical), Principal Component Analysis, Factor Analysis, etc. 5. Statistics - Hypothesis Testing, Statistical Simulations, Cross-Validation, Regularization, Various Distributions, ANOVA, Meta-Analysis, etc. 6. Programming - Python, R, SAS, and SQL Technical Blog: https://leihua-ye.medium.com YouTube Channel: https://www.youtube.com/channel/UCBBu2nqs6iZPyNSgMjXUGPg Contact: yeleihua@gmail.com