- Built hundreds of classification and anomaly detection models to provide warnings and real time feedback for a variety of customer use cases that require deliberation on optimal algorithm selection, hyper-parameter tuning, variable selection, and data cleansing techniques to be applied.- Developed and optimized the code pipeline for machine learning products. This included conducting R&D on new product features, engaging in bug identification and resolution processes, and contributing to… Show more - Built hundreds of classification and anomaly detection models to provide warnings and real time feedback for a variety of customer use cases that require deliberation on optimal algorithm selection, hyper-parameter tuning, variable selection, and data cleansing techniques to be applied.- Developed and optimized the code pipeline for machine learning products. This included conducting R&D on new product features, engaging in bug identification and resolution processes, and contributing to QA efforts for application updates and fixes.- Presented machine learning use cases and collaborated with customers to address a variety of industry needs using Falkonry’s AI platform. This included customer site visits with application training and tutoring on machine learning subject matter and terminology.- Utilized AWS cloud platform tools such as boto3, S3, Rancher, Kubernetes, and Docker for the management of a machine learning pipeline for experimental neural network models and product code contributions.- Developed and implemented geographical models for density estimation and predictive object tracking that was visualized in Kepler using H3 grid data- Wrote Python code and used Rest API for automating data engineering tasks, generating reports for sharing findings with customers, and other automatable tasks within a developing application. Many of these automations became tools for employee use, customer use, or integrated into the product. Show less

- Implementing Keras neural net models for both classification and regression purposes on time-series data- Computing reliability and performance metrics with data collected from athlete force plate tests- Python and R development to support company data analysis needs- Write scripts to interact with AWS cloud services such as S3 and Sagemaker

- Made appointments and prepared schedules for student advisors- Updated records and maintained an organized filing system for student information

- Conducted market analysis for new companies in the corporate wellness sector and competitors- Participated in case study analysis and displayed data for the wellness activities market- Made connections with potential customers and helped coordinate events