Python Developer with AI/ML at State Street

Developed a highly efficient ETL process using Python and SQL to load data from multiple sources, enabling timely and accurate analytics. Implemented regression models to forecast business outcomes on structured datasets and optimized decision-tree classifiers for feature selection and interpretable predictions. Built and maintained Python applications using Django, Flask, and Pyramid, and developed multi-threaded web services with CherryPy and Web2py. Managed cloud-based deployments in Azure, tracked service issues, and implemented CI/CD pipelines using Docker and AWS ECS. Built and deployed Random Forest and XGBoost models to improve classification accuracy on high-dimensional data, and leveraged LangChain to orchestrate LLM workflows in production AI pipelines. Conducted comprehensive testing with Pytest and Jenkins to ensure code quality and stability.

Python Developer with AI/ML at Groovy Webs

Built Named Entity Recognition pipelines to extract domain-specific entities from unstructured text. Worked with Generative Adversarial Networks (GANs) to generate synthetic image datasets for model training. Developed RESTful services using Flask, and performed data preprocessing with NumPy and Pandas. Built data visualization dashboards in Tableau and connected to MySQL via a Python-based database connector. Contributed to deployment on Google Cloud Storage and collaborated on hyperparameter tuning with GridSearchCV and RandomizedSearch. Assisted in code reviews and used Git for version control.