Develop and deploy new features in mobile and desktop Angular web applications that increase apply rates and top-line revenueInstrument front-end A/B tests that provide rapid, low-risk evaluation of critical features in real-world environmentsLed an organization-wide transition from one Analytics and A/B testing vendor to another, pivoting to a lighter-weight solution that reduced cost by 90%Researched consent-management platforms and managed site-wide integration to comply with US privacy regulationsMentored junior team members on programming best practicesDeveloped a wage-parsing algorithm that increased apply conversion by 15% and jump-started a push for pay transparency in hourly job postingsDesigned and implemented an end user knowledge graph in AWS Neptune, providing real-time job recommendations to job seekers based on behavioral patterns – a capability that’s resulted in > 500% ROICreated data streaming pipelines in Confluent Kafka to hydrate the knowledge graph and provide in-session user recommendations

Participated in a company-sponsored Leadership Development Program, which required a rigorous application and recommendation processDeveloped and maintained the deployment and measurement MLOps pipelines for data science models, allowing Data Scientists to iterate on predictive models more efficientlyDesigned Python APIs intended to interface with and update postings dataSpearheaded and productionalized a random forest model using principal components analysis for dimension reduction to pinpoint fraudulent postingsManaged Snowflake user roles and monthly auditing and clean-up of unused tables and schemas

I grade assignments for BAS 474: Data Mining, hold office hours to answer students' questions, and respond to any issues they may have with learning to program in R.

I programmed a roster optimization application to maximize expected wins while adhering to salary cap restrictions, created dynamic dashboards that blended R and Tableau to predict playoff appearances based on certain team characteristics, and leveraged machine learning techniques to model player contracts amounts.

I planned and executed programming for 60 scholars, including cultural lectures, retreats, and community service activities. One of my biggest responsibilities was helping organize Haslam Scholars Selection Weekend to select the next class of 15 scholars.

I greeted guests at the UT Honors and Scholars Programs Office, fielded student/parent questions, and assisted Honors faculty and staff in any administrative tasks they needed to complete.

I analyzed data to inform scouting and recruitment procedures, and designed/conducted studies to test current notions about game-time decisions, such as coin-toss deferment and fourth down strategy.

I conducted correlational studies analyzing possible connections between player psychological measures and both on-field performance and off-the-field behavior. I also worked to develop better metrics for scouting procedures and draft decisions. Finally, I created an encyclopedia of current football research, so that colleagues could quickly find any article that relates to their desired topic.

I performed ad hoc data queries (using SQL) for various departments within the company, as well as created and distributed data visualizations using Pyramid Data Analytics Software.

I proctored exams and helped Dr. Frank Guess prepare for his lectures.

I served as both a sandwich artist and supervisor, with responsibilities including training new employees, performing inventory checks, and balancing the cash register at various points throughout the work day.