Python Budget Forecasting Analyst

I have a collection of financial records and I want to transform them into clear, reliable budget forecasts with Python. The core of the job is data analysis—no scraping or automation—so every effort should go into cleaning the figures, choosing sound statistical techniques, and presenting easy-to-interpret results that help me plan. You’ll work with standard CSV exports (date, category, amount, and a few custom fields). I’m open to whichever Python stack you prefer—pandas, NumPy, statsmodels, scikit-learn, or even Prophet—as long as the code is well-commented and reproducible in a fresh virtual environment. Here’s what I need from you: • A self-contained script or notebook that ingests my raw data, handles missing values, detects outliers, and generates forward-looking projections. • Clear visualizations (matplotlib or seaborn are fine) that highlight spending trends and the forecasted range. • A concise written summary explaining the assumptions, the chosen model, and how to tweak inputs if my data structure changes. I’ll send a small anonymized sample first so you can confirm the approach, then the full dataset once we align on the methodology. Accuracy, transparency, and clean code matter most; if your model meets those standards, I’m ready to move quickly.

Project ID: 40593742