- Developed and deployed machine learning models to rank candidates for job applications, improving the hiring process efficiency by 30%.- Utilized supervised learning techniques to build classification models for customer segmentation, achieving an accuracy of 92%.- Implemented unsupervised learning algorithms to identify hidden patterns in customer purchase data, leading to a 15% increase in sales through targeted marketing.- Designed and developed recommendation systems for product suggestions, enhancing user engagement by 25%.- Applied deep learning methods to optimize neural networks for image recognition tasks, achieving a 95% accuracy rate.- Conducted feature engineering and selection to improve model performance, using techniques like vectorization and normalization.- Evaluated model performance using metrics such as precision, recall, F1 score, and ROC curve.- Collaborated with cross-functional teams to integrate machine learning models into production systems.

- Assisted in developing predictive models for customer churn analysis, resulting in a 20% reduction in churn rate.- Conducted exploratory data analysis and visualization to uncover insights and trends in large datasets.- Implemented natural language processing (NLP) techniques for text classification tasks, improving the accuracy of sentiment analysis models by 10%.- Participated in model validation and testing to ensure robust and reliable performance.- Worked with stakeholders to understand business requirements and translate them into technical specifications for data projects