• Developed an LLM pipeline leveraging a ChatGPT-based API that can generate precise and comprehensive document analysis for over 1,000 pages of environmental policy, which has savings potential of up to $400,000 for The Nature Conservancy in consulting fees.• Wrote a research paper about the experimentation (Prompt Engineering, LangChain, Fine-Tuning) process for LLM MLOps.• Developed PyTorch neural network-based object detection algorithms and workflows to classify the species in over 30,000 images (60 GB) stored in AWS buckets. The algorithms are deployed here. (I worked 16 hours/week for this role).• Co-Developed WellWatch, a Plotly-Dash application powered by AWS that updates daily via GitHub Actions.

• Instructed over 70 students and led office hours sessions for a course that covered a variety of Data Science skills including Python, SQL, Tableau, APIs, HTML5 and Machine Learning• Graded the students’ projects and gave constructive feedback

• Consulted the CDC as a member of the Data Analytics and Visualization task force. Helped optimize the CDC’s workflows by applying best practices in Data Structures and Algorithms.• Used Spark Python and Spark SQL in Azure Databricks notebooks to extract data from 10 Terabyte datasets and construct 3 machine learning workflows that provided logistic regression analysis for projected COVID severity.• Constructed ARIMA models based on time series data to project future COVID cases based on seasonality.• Created public-facing dashboards with PowerBI that covered the entire United States.• Coauthored a publication in Morbidity and Mortality Weekly Report (the CDC’s primary research journal).

• Tasked with transitioning data from Namely to Workday, and generating analysis of the past data• Ran advanced Excel operations to clean/organize data and prepare it for upload to the new Workday platform• Wrangled HR data with SQL queries from Namely into Excel