• Responsible for pulling high-impact data on a daily basis for internal teams including marketing, product, and more, helping to create new data-driven product features, enrich articles through data storytelling, and advance business development.
• Fulfills client requests on a weekly basis, including building streamlined and automated dashboards, addressing research questions through data exploration, and evaluating new external data sources.
• Main analyst for the Chartmetric Year in Music Report, pulling hundreds of queries and managing pipelines to ensure high data quality across all elements of the report.

Tools used:

• SQL
• Python
• Snowflake / RDS
• Hex
• Looker

• Produced valuable predictive insights for IGS Energy Home Warranty Claims.
• Built a predictive statistical model from raw data using Python, and presented relevant findings and suggestions to business stakeholders.

Tools used:

• R
• RStudio
• Canva

• Presented valuable customer segment insights to The Ohio State University’s Office of Advancement.
• Produced robust statistical insights and business strategies from raw data in R.

Tools used:

• Python
• Jupyter Notebook
• Canva

Internship experiences:

• Worked on the data strategy team on personalization projects, using insights collection on customer data with Snowflake to develop strategies and hypotheses for A/B testing to implement new features and experiences for users across all channels (email, app, push, browser).
• Optimized web analytics tag management database architecture, improving the method of storing neccessary metadata on tag data from hundreds of sources, including Google Analytics.
• Completed both a final personal project and cross-functional case competition, presenting to a panel of judges of various levels across the company, utilizing both techincal and personal presentation skills.

Tools used:

• SQL
• Snowflake
• Adobe Analytics
• PowerBI
• Google Analytics
• Excel

Internship Experiences:

• Wrote 3D visualization and animation tutorials in Python for new users of FURY, an international open-source scientific visualization project
• Implemented new shapes and functions to expand the FURY library using 3-dimensional calculus and linear algebra concepts with the help of Python packages such as NumPy and VTK9
• Used Git/GitHub heavily for making and editing pull requests

Tools used:

• Python (vtk9, numpy, pandas)
• Git/GitHub

Spring 2022 Experiences:

• Presented facial recognition research and DCiFR GUI software at the Population Association of America 2022 conference in Atlanta, Georgia. The presentation was entitled “Computer Vision and Applications in Social Science: Deriving Race and Gender From Photos” in the “Machine Learning Applications to Population Processes” session.
• Joined the openVA research group under Professor Sam Clark to begin working on projects related to demographic data, including building a relational database management system in SQLite for population data

Spring 2021 Experiences:

• Became confident in Python software development skills and researched PyQt packages to build a GUI connected to deep-learning facial analysis models
• First author of DCiFR project, creating and refining features including single image mode and batch mode, check box selection of multiple attributes, output and error messages for the deep learning model analysis, and formatted CSV results.

Spring 2020 Experiences:

• Mastered web-scraping with Python and was able to experience the full process of data analysis, from collection and organization to statistical regression analysis
• Learned about facial recognition software, sentiment analysis, and natural language processing
• Became interested in the social applications of data analytics practices, influencing me to pick up a minor in sociology

Tools used:

• Python (pandas, numpy, pytorch, deepface, fairface)
• R