Currently an Extern @ARCeH·🟢 Open to work
I'm Kimberly, a Data Analytics M.S. candidate interested in business intelligence, data management, and visualization. Let's innovate together!
Discover my work in data analytics, featuring projects in Tableau, Excel and health data analysis that showcase my skills and commitment.
This Excel project analyzes historical Kaggle data to evaluate Bitcoin's price trends and market volatility. Key findings highlight a strong correlation between daily highs and lows ($R^2 = 0.983$) and reveal that Bitcoin closed lower on 52% of trading days despite surging from $30,000 to $60,000+,
This interactive Tableau dashboard analyzes global COVID-19 death trends using public data to highlight regional impacts over time. Featuring dynamic filters for country, region, and timeframe, it visualizes key metrics such as total deaths and mortality rates through maps and time-series charts to
I'm Kimberly, a Data Analytics M.S. candidate interested in business intelligence, data management, and visualization. Let's innovate together!
M.S. Data Analytics candidate with experience in data analysis, cross-functional communication, systems thinking, and sensitive data management. Seeking to combine skills in SQL, Python, Tableau, Power BI, Excel, and translation of complex data for operational improvement and decision-making. Mandarin Chinese proficiency ensures I am suited to support global, diverse teams.
Externships
Data Analytics, Health Outcomes Externship with ARCeH
In progress
Experience
Data Analytics Health Outcomes Extern
ARCeH (Advancing Research for Children’s Health) · Aug 2026 – Nov 2026
Member Experience Manager
Weekend Health · Jan 2024 – Feb 2025
Health Coach
Noom Inc. · Sep 2019 – Nov 2022
Education
Eastern University
MS, Data Analytics · Class of 2027
University of Wisconsin-Madison
Transfer Credit, Business Analytics
University of Florida
BS, Family, Youth and Community Sciences
Skills
This Excel project analyzes historical Kaggle data to evaluate Bitcoin's price trends and market volatility. Key findings highlight a strong correlation between daily highs and lows ($R^2 = 0.983$) and reveal that Bitcoin closed lower on 52% of trading days despite surging from $30,000 to $60,000+,
This Excel project analyzes historical Kaggle data to evaluate Bitcoin's price trends and market volatility. Key findings highlight a strong correlation between daily highs and lows ($R^2 = 0.983$) and reveal that Bitcoin closed lower on 52% of trading days despite surging from $30,000 to $60,000+, demonstrating how long-term growth persists alongside frequent short-term pullbacks.
This interactive Tableau dashboard analyzes global COVID-19 death trends using public data to highlight regional impacts over time. Featuring dynamic filters for country, region, and timeframe, it visualizes key metrics such as total deaths and mortality rates through maps and time-series charts to
This interactive Tableau dashboard analyzes global COVID-19 death trends using public data to highlight regional impacts over time. Featuring dynamic filters for country, region, and timeframe, it visualizes key metrics such as total deaths and mortality rates through maps and time-series charts to surface critical patterns and high-severity areas.
✅ Verified by Extern · ⏱️ In progress
Here’s what the data says: put a pin in Bangkok. Draw a five-hour flight radius around it. You just circled half the world's population. And half of those people are kids under five, an age where survival itself isn't guaranteed. Five isn't an arbitrary number: it's the line researchers use as a proxy for a country's overall health, because almost every preventable childhood death, driven by a bad water source, poor air quality, or an infection nobody caught in time, happens before it. Clear five, and the odds of reaching adulthood jump astronomically. Don't, and the cause almost always traces back to poverty, healthcare access, environmental risk, or nutrition, something that could have been mapped, measured, and prevented in time. That's the gap this externship exists to close: turning scattered, messy public data into a specific, defensible answer about what's actually driving that risk in a given place, and pass it to the people at ARCeH who want to know about it.
The externship converted public health, environmental, and demographic data into an analytic foundation for understanding under-five mortality drivers in the Bangkok region. The work reviewed data sources and analytical limits, defined suitable correlational approaches, and produced a structured plan for measuring associations between environmental, access, and nutrition indicators and child
I located and validated a merged dataset of 26,778 child records that included paired Enterococcus exposure and gastrointestinal outcome variables using a six-point fitness checklist.
I searched for children's environmental health data, evaluated a merged beachgoer dataset using a six-point fitness checklist, and confirmed it passed all criteria. The file contained 26,778 child records with paired Enterococcus exposure and GI outcome variables.
