Data Scientist
Lynker Technologies
May 2021 - current / Santa Barbara, CA

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• Designed reproducible methods for data sourcing, extraction, transformation and visualization in Python/R

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• Managed and maintained project code bases using GitHub, emphasizing collaboration and communication with cross-functional teams

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• Reduced processing times for an internal batch data processing workflow by creating a CI/CD pipeline that triggers a batch data processing event in AWS using Git, Python, S3 SQS, and Lambda

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• Developed and deployed highly available interactive data dashboards written in Python/R (Flask/Shiny) and deployed using GitHub Actions, AWS CodePipeline, and AWS Elastic Beanstalk

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• Achieved project goals while improving coworker workflows by creating and maintaining open-source packages in Python/R

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• Provided a client with a predictive streamflow forecasting model using an XGBoost model using the R “tidymodels” machine learning framework

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• Improved inefficient and outdated report generating scripts by refactoring them using R Helped develop microservice frameworks and CloudFormation templates to make it easier to manage and deploy AWS services

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• Created a workflow that allows coworkers to easily use and deploy there R code to AWS Lambda functions using Docker and Elastic Container Registry

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• Provide coworkers with code refactoring, review, and debugging​