Hire Kaelan N. - Forward Deployed Engineer

* Full stack engineer with experience: * Developing desktop and web applications, * Designing and implementing cloud backend architecture within AWS and GCP * Constructing a data processing pipeline for IoT medical devices * Leveraging ML techniques for both prediction and classification

* Created a data pipeline for the collection, storage, annotation and modeling of police audio data within the Microsoft Azure environment * Trained both a Random Forest model (92% accuracy) and a time-series logistic regression model (85% accuracy) * Currently working with UC Berkeley professor Dacher Keltner to determine if police bodycam audio can predict police aggression * Developed an annotation tool and UI to streamline the process of annotating audio clips for features of aggression * Used statistical methods including one-way anova, PCA and k-fold cross validation to extract statistically significant audio features