Alexandra Juravet

I’m a recent graduate in Cybernetics, Statistics & Economic Informatics, and I build quantitative pipelines for forecasting, financial risk modeling, and data-driven decision support. My thesis work centered on time series analysis of stock market returns, including volatility modeling and dynamic Value-at-Risk.

I’m comfortable turning messy data into reliable models using R and time-series techniques such as ARIMA/ARFIMA and GARCH-family specifications, alongside dynamic risk estimation. I also extend analyses into multivariate frameworks with cointegration, VAR/VECM, and Granger causality, then compare forecast accuracy with statistical tests.

Beyond risk modeling, I’ve developed SQL- and dashboard-driven workflows to support business questions—building relational query structures and interactive Excel dashboards, including Monte Carlo simulation for revenue risk. I also explore statistical classification and clustering (e.g., logistic regression, decision trees, KNN, and neural networks) to segment and categorize economic data.

What I value most is analytical rigor with practical impact: I like clear assumptions, testable outcomes, and communication that helps stakeholders act. I’m now looking to apply my data, risk, and financial analysis foundation in a junior role where I can contribute and keep improving through real-world projects.