Noah J. Email and Phone Number

Collaborated and contributed to code bases for clients on a wide range of projects ranging from web applications, robotics, game design, and backend Python engineering.Provided expert technical advice and consulting services to clients in the areas of computer science, software development, and information technology, with a focus on robotics, A.I., VR, and mobile game development.Conducted research and analysis to understand client needs and develop solutions tailored to their specific requirements to create unique and innovative solutions.

Led the design and development of a RESTful API using Python to synchronize deliveries for shippers and carriers, resulting in a reduction of unnecessary delivery truck stops by 30%.Utilized Google Cloud Platform (GCP) and Jenkins to deploy and maintain the API in a scalable and efficient manner, resulting in increased reliability and uptime.Worked closely with cross-functional teams, including logistics and sales, to gather requirements and ensure successful implementation of the API.Integrated machine learning models into the real-time data processing workflow, enabling predictive analytics for the purpose of optimizing limited computational resources.Collaborated in the development of an A.I. system that accurately predicts which orders can be combined and shipped together, resulting in a 20% increase in order consolidation efficiency.Designed and implemented gcloud automation python tooling that reduced company-wide workload by 90%.

Designed and implemented a robust data processing pipeline to handle real-time data sets, ensuring timely ingestion, validation, and transformation of customer address data.Developed and implemented a data cleansing tool using Python to ensure the accuracy and completeness of warehouse and sales data, resulting in a 95% reduction in errors.Designed and implemented MySQL database to store cleaned data, improving data retrieval time by 40%.Developed and maintained ETL scripts using Python to transform raw data into a format suitable for analytics, reducing data processing time by 75%.Collaborated with cross-functional teams to understand business requirements and optimize the data cleansing tools, resulting in a 60% increase in productivity and a 40% reduction in manual data cleansing efforts.Monitored data quality metrics and performed regular audits using Python to identify and resolve data quality issues in a timely manner, resulting in a 90% improvement in data accuracy and completeness.