Main engineer of a Python-based backend for a web application enabling scientists to analyze and interact with genetic variant data. Designed and implemented RESTful APIs for efficient data retrieval and updates in SQL databases using SQLAlchemy. Integrated backend functionality with a TypeScript-based UI. Orchestrated continuous deployment pipelines with Azure DevOps, leveraging Nginx and Gunicorn on Linux servers. Optimized SQL database design and management to ensure effective data organization and accessibility. Applied advanced algorithm design and software architecture principles to deliver a scalable, high-performance solution aligned with business objectives.

Headed development of a modular Docker-based application streamlining automated testing of

bioinformatics pipeline metrics and Laboratory Information Management Software APIs and databases. Leveraged Azure DevOps to architect and execute pipelines, while creating informative dashboards to

present results and diagnostics derived from application execution. Collaborated with multiple internal and external development teams to add new functionality and integrate existing applications into the automated QA infrastructure.

Research relating to the possible relationship between kinesin motor activity and tubulin post-translational modifications. Developed microtubule breaking functionality for open-source cytoskeletal simulation software, cytosim, to reflect results seen in in-vitro experiments. Utilized C++, R, and bash scripting.

Data and statistical analyst for a study correlating the symptoms of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) to post-acute COVID-19 symptoms. Analysis consisted of principal component analysis (PCA), which allowed us to identify symptom clusters among a patient population.

Performed data analysis for a published paper which investigated the usage of Aripiprazole as a potential treatment for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS).