Established Quality Tolerance Limits using statistical analysis and clinical trial methodologies, reducing trial invalidation risks, ensuring safety and efficacy, and enhancing reliability, as demonstrated by a global CRO employing this tool across four clinical trials, resulting in a 20% improvement in trial efficiency.Developed and utilized an internal Natural Language Processing tool to streamline data management by matching, comparing, and cleansing similar site-level data across a database of 10,000+ entries, which improved data accuracy by 30% and reduced data validation time by 50%.Instrumental in the creation of a pre-study enrollment forecasting model that employed Monte Carlo Simulations, Gamma-Poisson distributions, and Maximum Likelihood Estimation functions which became an industry-leading tool, outperforming competitors by 40% in modeling enrollment rates across various clinical trials based on phase and indication.

Deployed a recommendation engine to conditionally recommend Forms and Questions to Clinical Trial Builders based on Questions entered, decreased the variance of new forms and questions by 10%.Spearheaded a Diversity, Equity, and Inclusion (DEI) project, conducting sophisticated statistical analysis on demographic data related to clinical trial participation. Identified patterns and trends that provided insights into demographic propensities for trial participation, supporting the development of strategies to promote greater diversity and inclusivity within trial participant populations.

Standard Reports: Identified and Created a set of 12+ reports that could be reused for all Clinical Trials, created documentation, use cases, and a library of SQL Queries to build out reports for different scenarios. This resulted in an expedited reporting process by 10x.Compiled and Analyzed data surrounding Protocol Deviations for all Clinical Trials in the company, created a pipeline for a dashboard, and delivered KPIs to clinical trial sites to uncover trends in the protocol.

• Served in an integral role by consulting undergraduate students, graduate students, and faculty on how to integrate data science into their own research projects or course material.• Closely collaborated with the College of Engineering and Library staff to organize and facilitate a data visualization workshop for 150 students.

• Played a key role by spearheading the development of new methodology on how to calculate national school connectivity goals. Performed a presentation on findings to the CEO, where it was included in our National State of the States Report.• Leveraged expertise in the development of a Python tool to allow for the delivery of data on current broadband and school connectivity goals to the state governor’s office. Efforts resulted in the process being expedited by 5000%.

• Conducted extensive data analysis and administered documentation, testing, and implementation of tools and support for national analysis. • Mined internal data and data from Non-profit DonorsChoose; identified a correlation between schools that were given high speed internet and new technology projects.