As a DevOps Engineer, I have worked on a multitude of projects to get AnyVan's system onto the Cloud. - I have used Terraform codes to automate the creation of various AWS resources. For example: + Produced handcrafted Lambda functions for a variety of purposes such as Lambda@Edge functions to ensure that website traffic flows smoothly as well as cron-based Lambda functions to update Google Sheets with MySQL data for various business purposes. + Created Cloudfront distributions to manage AnyVan's websites as well as WAF rules to protect our assets. + Initialize autoscaling groups to set up MySQL EC2 instances using a shared EBS volume for our database. As well as migrating our MySQL EC2 instances to Aurora clusters. + Move our legacy codebase onto Dockerized containers to allow for a scalable, easy-to-manage infrastructure. I have worked extensively in a team-based environment utilizing agile practices to ensure ease of completion for projects in a timely manner.I have also led a course in our company about the advanced usage of Google Sheets. This covered topics such as Google Scripts, Python integration, and advanced Google functions in Python.

- Designed and implemented operational and business data analysis projects including: + Predictive desirability model for contract driver’s interest in job routes which greatly increased route allocation probability + Conversion of route allocation program from Google Sheets into Python, resulting in a decrease in processing time from over an hour to less than 10 minutes + Created, trained, and implemented a neural network with PyTorch in order to model and predict the number of journeys per day, number of jobs per day, and amount of views and expressions from all drivers per day + Reverse engineered competitor’s pricing formulas for strategic analysis + Analyzed regional job pricing strategies to optimize profitability, bolstering profit margins by ~9% with minimal changes + Created predictive operation model to optimize journey efficiency and profitability through the placement of flexible delivery jobs- Extensively used Python, Pandas, NumPy, and Matplotlib through complex data analysis projects as well as the creation and testing of industry critical programs- Implemented SQL queries to ascertain trends in data- Gained a strong foundation in PyTorch machine learning

- Extensively used Python, Matplotlib, NumPy, and Pandas to analyze large quantities of data whilecreating a predictive model to find trends in the data- Presented results in a coherent report and presentation- Analyzed a large quantity of data with over 200,000 data points from Kepler Telescope

- Extensively used Python, Matplotlib, NumPy, Pandas, and IDL to research various astronomicalphenomena using large array of datasets- Culminated in five different research projects with a focus on: + Creating models of real-world systems + Examining trends in a vast quantity of data- Presented results in peer-reviewed papers as well as professional presentations