This dynamic Senior Algorithms and Machine Learning Scientist with a doctoral degree has more than 3 years of experience in data science and programming. Recent experience includes developing a platform for data mining, data visualization and analytics. Systems experience includes Python, PySpark, SQL, PySpark, Bash, Linux, Azure, Databricks, Docker, Kubernetes, FastAPI, Git and PyTest.

Additional qualifications include:

• Served as a key machine learning engineer in the production of a drug inventory model, forecasting demand using time series analysis and gradient boosting, saving $250 million across more than 8600 stores
• Reduced prediction request times from multiple hours to seconds through refactoring of the model serving API code to run on Spark clusters
• Saved more than 100 monthly working hours by designing and implementing an end-to-end data pipeline for continuously ingesting and processing CSV and Excel files
• Developed the backend of a model serving API that pulled and transformed data from Azure DataLake and deployed it on Azure Kubernetes Services, including updating YAML files and creating SSL certificates, allowing the operations teams to make multiple prediction requests daily