Machine Learning / Data Science / Python Expert

We are looking for an experienced Machine Learning Engineer / Data Scientist / Python Developer to work with our team on ongoing AI, Machine Learning, predictive analytics, and data science projects. This is an hourly freelance engagement with the possibility of long-term work for candidates who demonstrate strong technical skills, reliability, and the ability to independently solve complex data problems. Our projects involve working with real-world datasets to develop predictive models, analyze customer/business behavior, automate data-processing workflows, improve existing models, and translate analytical results into actionable business insights. Key Responsibilities The selected freelancer may work on one or more of the following areas: Develop, train, evaluate, and optimize Machine Learning models Build classification, regression, propensity, lead-scoring and forecasting models Perform exploratory data analysis (EDA) Data cleaning, preprocessing, transformation, and feature engineering Feature selection and statistical analysis Work with large structured and unstructured datasets Develop reusable Python scripts and analytical workflows Build and improve predictive models using Scikit-learn, XGBoost, LightGBM, TensorFlow/PyTorch, or other appropriate frameworks Perform hyperparameter optimization and model comparison Handle imbalanced datasets and prevent data/target leakage Evaluate models using appropriate business and technical metrics Perform model explainability using SHAP, feature importance, or similar approaches Develop time-series and forecasting models where required Create data visualizations and analytical reports Debug and improve existing Python/ML code Review existing models and recommend improvements Develop model inference/scoring pipelines Document code, methodology, assumptions, and results Collaborate with our internal Data Science and AI team Required Technical Skills We are particularly interested in candidates with strong experience in: Python | Machine Learning | Data Science | Predictive Modeling | Pandas | NumPy | Scikit-learn | XGBoost | LightGBM | SQL | Statistical Analysis | Feature Engineering | Model Evaluation | Data Visualization Additional experience in the following would be valuable: TensorFlow / PyTorch | NLP | Generative AI | LLMs | Time-Series Forecasting | ML Pipelines | APIs | Cloud Platforms | MLOps | Git/GitHub Who We Are Looking For We are not looking for someone who only knows how to run pre-built ML notebooks or generate code using AI tools. We are looking for someone who understands the fundamentals behind model development and can independently determine: Which modeling approach is appropriate and why How to identify meaningful features How to detect data leakage How to handle class imbalance How to select appropriate evaluation metrics How to determine whether a model is overfitting How to improve model performance without compromising generalization How to translate model results into meaningful business recommendations Strong Python programming and debugging skills are essential.