I'm looking for a skilled data scientist or machine learning expert to develop a predictive model that estimates house prices based on key property features. The dataset includes information such as the number of bedrooms and bathrooms, living area, lot size, neighborhood, and other relevant details. Ideal candidates should be proficient in Python, data preprocessing, feature engineering, and regression or advanced ML models. Deliverables include a documented script or notebook with clear explanations, predictions, and insights from the data. The file has approximately 21,613 rows (entries), representing individual house sales. Data types are mostly numeric (integers/floats for measurements) with a few strings (e.g., id, date, zipcode). No missing values are evident in the provided sample, but full verification would require further checks. What I need from you: - Data cleaning and preprocessing - Provide visualizations to highlight key insights - Encode categorical variables - Train predictive models using regression or advanced machine learning algorithms - A documented Python notebook or script that can predict house prices, includes visualizations, model evaluation, and actionable insights from the dataset.