Aagyapal K•••

About

On the record

Currently, I serve as a Data Engineer at Aposys Technologies, where I am responsible for the comprehensive management of geotechnical and environmental data. My role includes: Data Cleaning and Preprocessing: I carefully clean and preprocess complex datasets to ensure their accuracy, consistency, and usability for analysis. Data Storage and Management: I manage the storage of large volumes of geotechnical and environmental data on Google Cloud Platform (GCP), making sure it is secure and easily accessible. Pipeline Development: I design and implement automated pipelines to streamline data processing, making critical information readily available for informed decision-making and analysis. In my previous role as a Machine Learning Practitioner, I leveraged over 1.5 years of experience to build and refine projects in computer vision, natural language processing, and time series forecasting using TensorFlow and PyTorch. Additionally, I served as a Teaching Assistant at Carleton University for 8 months, where I supported students in their learning journey. Effectively collected and managed 190 unbalanced datasets, addressing class imbalance through sampling techniques. Employed the BERT algorithm to transform 200K medical datasets from complex abstracts into simplified formats. Helped improve the overall scores of 100 computer science students by conducting class presentations, lab hours, and tutorials, and providing valuable feedback on their assignments and presentations. I am passionate about using my skills in both machine learning and data engineering to take on challenging projects. With experience in building strong data pipelines and a solid understanding of machine learning models, I can turn large datasets into valuable insights that support informed decision-making and drive innovation.