Jia Li Dong

Gates Millennium Scholarship Winner

As a proud Gates Millennium Scholar, I embody the program’s values of academic excellence, leadership, and community impact. This prestigious scholarship has not only supported my educational journey but also inspired me to strive for excellence in all endeavors. It has shaped me into a lifelong learner committed to using my skills and knowledge to create meaningful change. I had the honor of producing research on Gates Millennium Scholars with Dr. Barry Nagle and studying migration patterns of scholars along with post-graduate studies when financial barriers are removed.

Telework team efficiency as commended by DOD CADE

This is highlighted from Inside Defense publication article. During this time, I did a ton of data science and analysis work, from developing predictive analytics use cases for FlexFile cost data using time series and distribution fitting to leading the TIFF file conversion using Optical Character Recognition to convert and data scrape image files to actual data in R and Excel. Additionally, I've worked with the Software Resource Data Reports (SRDRs) to build a database in CADE that combines databases in CADE using R and cleaned data with data manipulation and natural language processing. I'm an expert at checking database consistencies, creating a series of criteria to rate data quality, and document anomalies with detailed descriptions.

Social Determinants of Health Research

I've produced several research on predicting and analyzing SDOH impact on cancer patients and have been invited to present on several Georgetown and MedStar Research Symposiums that has worked with ICBI. Many of the SDOH & cancer research includes oncology patients, immunotherapy research, HIV & Lung Cancer impact, elderly patient research, and palliative care. Read more on my research here with dashboards.

Data Scientist/Senior Analyst

Tecolote Research (January 2020 – Present)

As a Senior Analyst / Data Scientist at Tecolote Research, I delivered data science solutions under tight deadlines. My responsibilities included cleaning and matching CADE and DHS datasets using natural language processing techniques and ensuring data accuracy. I automated tasks such as converting TIFF files to Excel using Optical Character Recognition and performed data scraping for analysis. I designed and developed an R Shiny web application to streamline report generation and data entry processes. I also validated raw data input and export processes for AWS Redshift servers, documenting required data sources to ensure dataset integrity. My work relied heavily on R, Python, AWS Redshift, SQL, Tableau, and Power BI.

AI Trainer - Mathematics Expert

Handshake AI (January 2025 – Present) - Freelance Contract

In Handshake AI, I've developed and evaluated domain-specific prompts to assess the performance of large language models (LLMs) and analyzed LLM outputs for scientific accuracy, clarity, and depth in specialized subfields of Mathematics and Statistics. I've also contributed to improving AI understanding of complex Mathematics through expert review and feedback, and conducted independent research to support prompt development and evaluation tasks. My work relied heavily on understanding of LLMs, prompt generation, and AI modeling.

Data Analyst/Statistician Researcher - Freelance Contract

UNCF (July 2019 – November 2019).

During my time at UNCF, I produced comprehensive statistical studies to support scholarship goals. I analyzed 15 years of scholar migration data and presented my findings through advanced statistical modeling and visualizations. By leveraging tools such as R and Python, I provided actionable insights that guided scholarship program strategies.

Mathematical Statistician

U.S. Census Bureau (September 2018 – December 2018)

At the U.S. Census Bureau, I improved classification and sampling models, achieving a 50% increase in accuracy. My role involved analyzing over 20 GB of census data to develop predictive models for address frame updates supporting the 2020 Census. I prepared sampling frames that reduced error rates by 23% and conducted extensive statistical modeling to determine active and passive units in the Master Address File. I utilized R, Python, and SAS to accomplish these tasks.

Risk Management Analyst/Insurance & Actuarial Associate

Department of Insurance, Securities, and Banking (June 2017 – August 2018)

In this role, I streamlined operational efficiency, reducing labor hours by 400%. I applied advanced statistical methods to evaluate insurance rates, calculate medical reserves, and analyze factors influencing insurance ratings. Additionally, I developed R-based functions for reserve computations and conducted comprehensive data visualizations to support decision-making. My work demonstrated proficiency in R and Python.

Summer Undergraduate Researcher

Georgetown McDonough School of Business (May 2016 – September 2016)

As a summer undergraduate researcher, I conducted a cross-country comparative analysis of food safety regulations, summarizing findings in a detailed research paper. By applying qualitative and quantitative methods, I increased research efficiency by 200% and reduced external research time. This role involved significant data analysis and collaboration with peers, utilizing R for statistical evaluation.

Finance Associate

Downtown DC Business Improvement District (June 2014 – August 2014)

At Downtown DC Business Improvement District, I managed financial tasks such as processing accounting records, payrolls, and financial statements while ensuring compliance with accounting standards. I identified and corrected errors in invoices and revenue sources, improving the accuracy of asset accounting and financial reporting.

Bachelor of Science in International Business and Finance. Georgetown University McDonough School of Business

I started this degree in 2013 and graduated in 2017. During this time, I gained a strong foundation in risk management, financial modeling, and derivatives.

Master of Science in Mathematics and Statistics. Georgetown University.

I started this degree in 2017, right out of undergraduate, and graduated in 2019. During this time, I gained expertise in data analysis, machine learning, natural language processing, data mining, programming, and data visualization techniques.