Freelance Data Scientist for Price Prediction Model Development

Project Description: We are seeking an experienced freelance data scientist to develop a price prediction model for used cell phones, considering factors such as Covid, iPhone launches, the age of the model, and availability. The ideal candidate should have a strong background in machine learning algorithms, particularly Gradient Boosting Machines (GBM), and excellent communication skills. We require someone who can work independently, meet deadlines, and adapt to changing requirements with ease. Responsibilities: Collaborate with our team to understand the project requirements, objectives, and data sources. Develop a high-quality Gradient Boosting Machine (GBM) model for price prediction of used cell phones based on the given dataset. Perform data preprocessing and feature engineering, including encoding categorical variables and incorporating external factors such as Covid and iPhone launches. Split the dataset into training and testing sets for model evaluation and validation. Optimize the GBM model by tuning hyperparameters using techniques such as cross-validation and grid search. Evaluate the model's performance using metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared. Provide insights on feature importance and the impact of external factors on price prediction. Prepare clear and concise documentation of the model, including methodology, results, and recommendations for future improvements. Assist with the deployment of the model for making predictions on new, unseen data. Communicate regularly with the team to provide progress updates and participate in meetings. Requirements: Proven experience in machine learning algorithms and model development, specifically Gradient Boosting Machines (GBM). Strong knowledge of Python programming and relevant libraries, such as Scikit-learn, Pandas, and NumPy. Familiarity with data preprocessing techniques, feature engineering, and model evaluation metrics. Experience with handling time series data and incorporating external factors into predictive models. Excellent problem-solving, analytical, and critical thinking skills. Strong written and verbal communication skills, with the ability to explain complex concepts to a non-technical audience. Ability to work independently and meet project deadlines.