- Planned and led the refactoring and extension of a public facing transparency and data quality monitoring tool.- Integrated with the research team to build out a human interaction interface for a researcher’s novelhuman-in-the-loop anomaly detection algorithm.- Lead an initiative to patch 12 million data points in the production COVIDCast database.- Developed, reviewed, and tested several technical challenges for hiring new members.- Attended and actively engaged in hiring meetings to expand the team.- Supported, guided, and mentored new members of the team.

- Researched and troubleshot mechanical and electrical issues with animatronics and fog machines within the haunted house.- Designed a novel IoT device to enable staff to monitor the pressurized air usage of the animatronics in the haunted house as well as the running time of the air compressors.

- Ran campaign analyses to derive insights on the effectiveness of marketing strategies through A/B testing and treatment control analysis.- Integrated census tract spatial data to SQL to attach more granular demographic data to members.- Wrote an API ingestion script to pull Bitly click data by multiple dimensions in order to serve analytical dashboards for marketing campaigns.- Lead the project to integrate multiple processes onto a Linux server.

- Trained and deployed a machine learning model to filter out noise from incoming collisionnotifications from our telematics enabled insured fleets.- Write complex SQL queries, on platforms such as MSSQL, Impala, and Spark SQL, toconnect third-party telematics data to internal claims and policy information.- Use Python to call REST and SOAP APIs, transform, and upload data to SQL using storedprocedures in an automated fashion.- Created an Excel dashboard that used complex SQL queries to display telematics informationthat was obtained through the automated data pipeline. This dashboard provides insights intofleet activity to underwriters and risk management.- Use Python to derive insights from telematics data against insurance policy information. Thisis often done through the packages Pandas, Numpy, and SciKit-Learn.

- Worked with the predictive analytics team to develop a pricing model update for a specialtyvehicle product. This involved data analysis and visualization through R and Python, as wellas SQL queries to gather data for the pricing model.- Wrote a large Python script to split multiple gigabyte flat data files into data files with asmaller number of columns so they could be uploaded to our SQL server. This SQL uploadwas also automated through Python.- Developed a geographically enabled website with GeoDjango to query different geographicexposure layers based on radii of operation or GPS routes. This project used PostGIS, ageographically enabled PostgreSQL server. This project was also deployed on GCP throughthe app engine.

- Assisted multiple professors by grading papers, helping students one-on-one, and organizingsupplemental instruction periods for sections of classes that students struggle with.- Developed Python scripts to pull grades from reporting website and aggregate them into ausable format to send to the professors.

- Managed day-to-day help desk tasks.- Executed network infrastructure upgrades throughout campus.

- Developed a new module for FilePro to create Excel documents from scratch. This was donein a C89 standard of C. This allowed users to export records from this program directly toExcel. Deployed on a Unix System.- Worked on various bug fixes for FilePro.

- Diagnose and fix hardware issues with university and student Dell and Apple computers.

- Developed a dashboard to view and run ETL tasks through Celery in Python. This gave an at-a-glance system status to the IT Manager.- Created unit tests using Selenium for a Python-based website allowing the team to catch bugs before the website went into productio