I’m a full-time data scientist with 5+ years in analytics and 10+ years tutoring university students in statistics. I help undergrad, masters and MBA students understand core concepts, debug analyses, and complete assignments or projects in Python/R. My teaching is concept-first, example-driven and focused on reproducible code so you actually learn — not just copy answers.

Probability & distributions, sampling theory Hypothesis testing & confidence intervals Linear & logistic regression, multicollinearity diagnostics ANOVA, experimental design & power calculations Causal inference (DAGs, confounding, adjustment) Bayesian basics & hierarchical models Time series & forecasting (ARIMA, SARIMAX, Prophet) Machine learning essentials: feature engineering, Random Forest, XGBoost, model evaluation Hands-on coding in Python (pandas, scikit-learn), R, SQL, STATA, SPSS, Minitab Thesis/project mentoring, assignment walkthroughs, exam strategy, reproducible reports/notebooks