I’m looking for a data-savvy partner who can turn a raw set of finance-sector customer transaction data into clear, insightful storylines. My priority is descriptive analysis: I want to understand what has happened—patterns in spending, seasonal spikes, product uptake, and any anomalies that jump off the page. Here’s what I’ll hand over: • Raw customer transaction files (CSV/Excel). • A brief explaining column meanings, business context, and any compliance notes. Here’s what I’d like back: • A cleaned, well-documented dataset ready for future work. • An exploratory data analysis notebook or script (Python, R, or SQL) with comments so I can reproduce every step. • A concise slide deck or PDF report highlighting key metrics, visual summaries, and take-away insights. • (Nice to have) An interactive dashboard in Tableau, Power BI, or similar for quick stakeholder browsing. Please keep confidentiality top-of-mind, explain your methods clearly, and flag any data quality issues you uncover. If you’re comfortable with Python (pandas, matplotlib/seaborn) or comparable tools, and you enjoy storytelling with numbers, let’s get started.