I am a curious, solution-oriented Data Scientist seeking to assist end-to-end decision making. After earning a degree in Computer Science at the University of Georgia, I began using my programming skills at Griffin & Strong. I communicate with expert lawyers and economists who specialize in Disparity Studies and automate their research methodology using Python. So far, I've created unique data pipelines to clean and analyze three different government's procurement data. The final analysis now serves as a legal factual predicate. Please visit my website to see examples of my work.
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Griffin & Strong P.C., Data Scientist |
May 2020 - Current
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- Leads efforts to take on time consuming and costly problems using automation and machine learning
- Creates ETL pipelines for reproducible transformations of data
- Standardizes operating practices for efficient and validated research
- Mentors junior analyst in improving their analysis process
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Griffin & Strong P.C., Data Analyst |
Nov. 2018 - May 2020
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- Performs multifaceted analysis on collected data from governmental organizations
- Translates research methodology into software and adapts models to each organization's constraints
- Isolates data gaps and anomalies and cleans data for reproducible analysis
- Communicates with clients to collect data and present findings
| Disparity Analysis |
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The completed disparity analysis of the City of Chattanooga, Cuyahoga County, and Mecklenburg procurement data. The analysis is meant to serve as a factual predicate for proposed policy changes and inclusion programs. This includes everything from data collection to analysis. The findings were then presented to stakeholders within these organizations.
| Data Profiler |
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A Python software allowing non-programmers to take advantage of the open-source "pandas-profiling" library which creates comprehensive HTML summaries of raw data files. This summary includes data warning, missing values, and correlations. The front-end was built using PyQt and can run on any operating system.
| Equity Lib |
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A Python library containing pre- and post-processing algorithms for wrangling common problem patterns in Excel files. The primary problem solved is resolving entities in joined data systems and traceability of rule based decisions.
| Forecasting Avocado Prices |
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| PASSNYC: Data Science for Good |
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| University of Georgia |
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