- Employing ML and NLP methods on product, customer, and review data stored in Snowflake warehouses to encourage a purchase by displaying personalized reviews to potential customers- Utilizing data mining, SHAP, a Latent Dirichlet Allocation Model, and multiple logistic regression models to conduct sentiment analysis, data visualization, topic selection, and multilabel classification - Developing an automated pipeline and blackbox function in python and SQL to train a model to automatically select individualized reviews based on a customer’s motivations- Presented to senior leadership in Allbirds

- Working on the Fidelity Fund and Investment Operations team to streamline the process of how Fidelity receives and stores mutual fund and ETF data.- Developed an automated data pipeline to clean and conduct EDA on Fidelity mutual fund and ETF data through AWS Lambda, Fast API, and various python packages such as scikit-learn and seaborn- Built an NLP model using Sentence Transformers and Gensim to embed and calculate a cosine similarity matrix between two vendor datasets - greatly improving the efficiency of the vendor switching process- Pipeline currently reducing 6 months and $500k per vendor of manual work to 6 minutes and no cost- Practiced Agile methodology, used Jira, and presented work to senior leadership

- Built reusable, scalable infrastructure solutions using Jenkins to automate the deployment,maintenance, and monitoring of Pega applications hosted on Kubernetes AWS and Docker- Utilized Jenkins, Docker, Kubernetes, groovy scripting and various other DevOps technologies- Presented work to senior leadership and Pega Community of Practice.- Utilized Agile methodology as well as became Scrum master.

Used sentiment analysis on tweets containing the names of fortune 500 companies and developed ML models to correlate stock prices and predict change based on tweet count, likes, comments, shares, and average sentiment. Presented final product at the ULAB Symposium.

Created a Finance curriculum to teach a class of 35 middle school kids financial concepts like investing and portfolio management. Led the class with multiple teams to compete in SIFMA national competitions. Upon the success of the middle school program, started an elementary school program.