Currently an Extern @ARCeH
I'm Kimberly, a Data Analytics M.S. candidate dedicated to transforming healthcare operations through data-driven insights. Let's innovate together!
Discover my work in data analytics, featuring projects in SQL, Tableau, and Excel that showcase my skills and commitment.
This project analyzes Bitcoin’s historical market behavior using Kaggle cryptocurrency data to separate long-term trends from short-term volatility. Excel analysis found a strong relationship between daily highs and lows (R² = 0.983). Despite rising from $30K to over $60K, Bitcoin closed lower on 52
This project uses Tableau to analyze global COVID-19 death trends and show how the pandemic affected regions over time. An interactive dashboard allows users to filter by country, region, and time period to compare trends. Maps, time-series charts, and key metrics such as total deaths and death rate
ARCeH · ✅ 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.
I'm Kimberly, a Data Analytics M.S. candidate dedicated to transforming healthcare operations through data-driven insights. Let's innovate together!
I am an M.S. Data Analytics candidate with a background in healthcare operations, cross-functional communication, customer service, and managing sensitive client data. I have skills in Excel, SQL, Tableau, process improvement, and profesional communication in team environments. Additionally, I am proficient in Mandarin Chinese, which enables me to effectively support global and diverse teams.
Externships
Data Analytics, Health Outcomes Externship with ARCeH
ARCeH
Experience
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 project analyzes Bitcoin’s historical market behavior using Kaggle cryptocurrency data to separate long-term trends from short-term volatility. Excel analysis found a strong relationship between daily highs and lows (R² = 0.983). Despite rising from $30K to over $60K, Bitcoin closed lower on 52
This project analyzes Bitcoin’s historical market behavior using Kaggle cryptocurrency data to separate long-term trends from short-term volatility. Excel analysis found a strong relationship between daily highs and lows (R² = 0.983). Despite rising from $30K to over $60K, Bitcoin closed lower on 52% of days. Visualizations highlight trends, volatility, volume, and investment risk.
https://1drv.ms/x/c/fca3933e4444e06c/IQCwYBZL00c_TaYeD2_8G0WZAVr09AkpT_JxYoN-ZYBkMqA?e=OA3ZzP
This project uses Tableau to analyze global COVID-19 death trends and show how the pandemic affected regions over time. An interactive dashboard allows users to filter by country, region, and time period to compare trends. Maps, time-series charts, and key metrics such as total deaths and death rate
This project uses Tableau to analyze global COVID-19 death trends and show how the pandemic affected regions over time. An interactive dashboard allows users to filter by country, region, and time period to compare trends. Maps, time-series charts, and key metrics such as total deaths and death rates make complex data easier to explore and highlight areas of greater severity.
https://public.tableau.com/app/profile/kimberly.aron/viz/CovidDeathsExploration/CovidDeathsDashboard
✅ 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 framed the analytical scope and constraints, clarifying which questions the available data could answer and which required different methods or data sources.
