I’m looking for a Python-savvy analyst to turn the numerical records stored in my databases into clear, actionable insights. The job centres on data analysis (not web development or automation scripting), so I need someone comfortable pulling figures directly from relational tables, cleaning them with pandas, and exploring them in depth. Here’s what I expect: • Connect to the existing databases (PostgreSQL and MySQL are the main ones) using Python, SQLAlchemy or your preferred connector. • Extract and clean the numerical fields, handling missing values and obvious outliers. • Produce an organised, well-commented analysis script or Jupyter notebook that walks through descriptive statistics, key correlations, and at least one statistical test or model relevant to the dataset. • Summarise findings in a concise report or notebook section with easy-to-read charts (matplotlib or seaborn is fine). • Deliver all code, a short “how to run” README, and any requirements.txt. I already have database credentials and can provide table schemas on kickoff. If you have a solid background in Python data analysis and SQL, I’d love to see a quick sample of similar work when you reply.