Data Scientist
CurrentMajor Duties : Machine Learning Model Development:Designed, trained, and deployed machine learning models for various business applications, including classification and regression.Implemented model evaluation techniques such as cross-validation, grid search, and hyperparameter tuning to enhance model performance.Collaborated with business teams to identify key metrics and develop models aligned with strategic objectives.Deep Learning Architectures:Developed deep learning models including CNNs for image processing and RNNs for time series prediction.Applied transfer learning to reduce training time and improve model accuracy for specific business problems.Conducted performance analysis and optimization for large-scale deep learning applications.Big Data Analysis:Utilized Apache Spark and Hadoop to process and analyze large datasets in a distributed computing environment.Built and maintained scalable data pipelines to handle real-time data streams and batch processing.Enhanced data processing workflows to handle petabytes of data while optimizing for speed and resource efficiency.Data Visualization:Developed interactive dashboards and reports using Python libraries (Matplotlib, Seaborn) to present data insights to stakeholders.Created visualizations to track key performance indicators (KPIs), improving decision-making for both technical and non-technical teams.Delivered data-driven insights that influenced business strategies and improved operational efficiency.Data Wrangling and Cleaning:Processed raw data from diverse sources, including structured, semi-structured, and unstructured formats.Cleaned, transformed, and merged datasets, ensuring data quality and integrity for model development.Applied feature engineering techniques to enhance model input and improve prediction accuracy.
