I’m looking for a data analyst who can take raw financial datasets off my hands and turn them into forward-looking insights. The task is strictly predictive: build a model that ingests the numbers I’ll supply, learns from historic patterns, and produces reliable forecasts I can act on. You’re free to choose the technique—time-series forecasting, regression, machine learning—provided the choice is well-justified and reproducible. I’ll provide cleaned CSV exports plus a brief data dictionary. From there I expect: • an exploratory snapshot that highlights key variables and any preprocessing steps • the core predictive model in Python (Pandas, scikit-learn or similar) with clear commented code • a concise report or slide deck summarising methodology, performance metrics, and practical recommendations Model accuracy, interpretability, and a workflow I can rerun in the future will be the main acceptance criteria. If you’ve done similar work in finance, please mention it so I can get a feel for your approach and turnaround time.