• Design Saas frontend and build backend infrastructure using R Shiny and MongoDB. • Maintain and update ETL procedures as well as build and implement new pipelines as needed. • Research solutions for ad hoc requests using Python, R, SQL, MongoDB, Cloud services. • Manage projects independently and meet consistent timelines. • Communicate with stakeholders and clients. • Perform data gathering and cleaning.

● Build dashboards and reports to help functional departments and executives keep a pulse ontheir areas of business. Key technologies may include Tableau, Excel, MS Office, and GoogleSuite.● Validate large amounts of data to ensure data quality in a variety of different ways dependingon the data and its consumer. Key technologies may include Python, Excel, and SQL.● Work with partners on efficient data processes while helping them keep their data as cleanas possible.● Utilize automation to create efficiencies and reduce resource allocation for routine tasks andprocedures. Key technologies may include Python, C++, Java.● Serve as the first level of support and triage for bugs and issues submitted by stakeholdersand customers.● Garner key insights from data and communicate these findings to key stakeholders to helpthem make data-driven decisions. Key technologies may include Python, R, Spark, SQL,Alteryx, Tableau, Power BI, Microsoft and Google suite of tools, Oracle.● Contribute to database maintenance and the implementation of data storage solutions byleveraging data modeling and database design methods● Leverage Machine Learning and Artificial Intelligence concepts and algorithms to createinnovative tools and processes within the company.● Help maintain a CI/CD pipeline for our data software to ensure we keep quality high and timeto market low. Key technologies may include Gitlab, Github, or Bitbucket.

● Produced two-dimensional material flakes for testing.● Optimized a method for making electrical attachments on two-dimensional material flakes for electrical testing and STM microscopy.● Perform laboratory tasks in a clean room environment while upholding lab standards.● Gained experience in a self-guided, laboratory work environment.

● Developed a classification model to identify astrophysical events.● Implemented an ensemble model to predict events from time-series data.● Achieved model prediction accuracy of ~78%.● Gained professional experience with Python, SciKit-Learn, Pandas, NumPy, and TensorFlow.