I will build python time series forecasting and econometric models

Turn your temporal data, sales history, and financial metrics into accurate, actionable predictive models.

Standard business analysis often fails when dealing with seasonality, volatility, and time-dependent trends. I build robust statistical time-series models and econometric forecasts in Python and Rhelping you anticipate demand, manage risk, and optimize planning.

What I Offer:

• Advanced Time-Series Modeling: ARIMA, SARIMAX, Prophet, Exponential Smoothing, and GARCH volatility models.
• Econometric & Multi-Variable Analysis: Feature engineering, lag analysis, and integration of external economic indicators.
• Data Preprocessing & Stationarity Testing: Unit root testing (ADF, KPSS), seasonality decomposition, and outlier cleaning.
• Model Evaluation & Metrics: Rigorous backtesting with RMSE, MAE, MAPE, and residual diagnostic checks.
• Deployment & Source Code: Clean Python scripts (pandas, statsmodels, pmdarima), Jupyter notebooks, or Streamlit app integration.

Why Work With Me?

• Computer Science & Statistics background with strong quantitative expertise (2nd place national credit risk modeling award).
• Focus on explainable, regulatory-aligned models over black-box outputs.

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