Kimberly L. Email & Phone Number

• Implemented a lesson planning system in Python. Used Terraform, AWS Serverless infrastructure, OpenSearch, Bedrock, and DynamoDB.• Developing a real-time speech-to-audio language translation application using C#/.NET backend and React.js frontend, hosted on Microsoft Azure, using Azure AI speech services.• Developed functionality for investment-focused site targeted towards international users, using React, TypeScript, and CSS. Implemented GraphQL queries, post-editing functionality, and mobile-friendly responsive UI based on Product feedback.• Developed a client-facing website showcasing machine-learning web applications such as translation and image processing. Utilizes Python, Django, HTML/CSS/Javascript. Hosted on AWS.• Collaborated with NYU professor and French researchers to develop a machine learning model for predicting plant species presence/absence at certain latitudes and longitudes, given climate data, soil data, and other local species observed.• Analyzed experimental behavioral science data using machine learning models such as XGBoost, TensorFlow, and SVM in Python to develop a new predictive model for behavior and performance.• Wrote combination image and text prompts to train an AI model on pattern recognition, mathematical problem-solving, and creative tasks.• Built website for users to buy and sell tickets utilizing PHP and MySQL, with ability to integrate with existing social media profiles.

Charlotte, Nc, Us

• Interacted with proprietary Quartz environment using QZDev to examine and make changes to Python code. Retrieved and examined data and tables from proprietary Sandra database.• Analyzed Python code for a report processing several million objects requiring high memory usage. Optimized code through benchmarking individual sections, reviewing logs, and rewriting resource-intensive sections to be more efficient, eliminating the need for daily manual intervention.• Studied the flow of multiple production-level cron jobs with interwoven dependencies to understand how data was reported and result files processed. Replicated the flow in non-production environment, improving testing procedures prior to deployment to production.• Analyzed resource-intensive Python cron job and discussed across teams ideas to reduce heavy load, including altering database object retrieval methods, adjusting cron job scheduling, and using or creating a more optimal index.• Collaborated across teams to implement new regulatory requirements, modifying existing Python scripts to extract additional data from proprietary object databases and integrate it into standardized feeds to be consumed by other teams.

Bachelor Of Science (Bs), Computer Science

Master Of Science (Ms), Computer Science