Data Analyst
Enhanced environmental data analysis through advanced machine learning techniques.• Developed end-to-end ML model using Python’s TensorFlow SSD packages to classify and measure the sediment profile, grain size, and biogenic structures in Sediment Profile Images (SPI).• Collaborated with engineers, geologists, and oceanographers to aggregate, normalize, visualize, and validate environmental and geospatial data to transition SPI classification model from a supervised to a semi-supervised algorithm, reducing SPI classification time by 80%.• Led the development and implementation of cloud-based databases and data collection systems, engineering scalable ETL processes that streamlined the firm’s data pipeline from source to dashboard.• Optimized data extraction, transformation, and loading processes from diverse sources, significantly enhancing data quality and accessibility, and enabling timely, accurate insights and visualizations for critical environmental reporting.