Engaged in thesis research by developing data processing pipelines to detect learning behaviors from joint handwriting and eye-tracking data captured from subjects performing cognitive tests to aid in the diagnosis of neurodegenerative disease.

• Supported the Product Management team in the design and development of data analytics and digital assets applications for the asset management industry.

• Investigated and documented the flow of financial data received by the firm’s portfolio companies in order to identify key pain points and improve overall data analytics operations.

• Conducted research, participated in 3rd-party product demos and compiled weekly reports on emerging start-ups and ongoing developments in generative AI with potential for integration into the firm’s AI strategy.

• Developed a software tool in Python that explores optimizing the allocation of assets into leverage facility portfolios aimed at maximizing various health metrics while adhering to covenant requirements.

• Worked as part of the engineering team to develop, improve and maintain a cross-platform full-stack application in an agile environment.

• Developed asynchronous Python scripts using celery in the Django backend (along with a suite of unit tests) that compute and update a Postgres database to support a highly requested customer feature.

• Delivered several major and minor UI/UX features using TypeScript and React Native in the web app frontend to enhance user engagement and experience.

• Updated GraphQL requests and introduced Python type checking as part of a larger strategy to mitigate errors and improve performance.

• Utilized geographic data from residential air quality dataset to capture additional demographic information to support further analysis.

• Led the creation of a dataset of air quality monitors listed on Amazon with information on cost, star rating, and customer reviews by utilizing web-scraping tools.

• Leveraged NLP techniques to develop topic models from the air quality monitor dataset to determine the factors and use-cases most significant to customers at different levels of satisfaction.