I am David Raymond Kearney, political economist by training, data scientist by profession.
As a data scientist, I create automated member and provider engagement campaigns that leverage e-mail, IVR, SMS and live calls to increase medication adherence.
I also design experiments and employ randomized control trials to improve campaigns by identifying the most effective campaign variants, and productionlize machine learning models to identify members at risk of behaving in a way that contributes to poor health outcomes and most likely to benefit from campaigns.
I got my Ph.D. at Duke University, where my research focused on applying econometric and statistical techniques to explain and predict the allocation of fiscal transfers.
This site, will cover spark, h2o. hive and data science using python.
Posts
Python Email Example
Using NewsPlease an open source, news crawler that extracts structured information
Creating a daily monitoring dashboard and database for the stockmarket with voila and datasette
Reading CSV from Datasette SQL Database
Maps and Folium
Stock Market Analysis of the S&P 500 Index using Simple Moving Averages and Exponentially-weighted moving averages
Stock Market Analysis of the S&P 500 Index
Text summarizer in Python, A Tale of Two Cities
Text summarizer in Python, Tieng Viet
EDA on Healthcare Data
Data Science Research Areas
Dask for Predicting Onset/Diagnosis of Chronic Conditions, Diabetes
Text summarizer in Python, Notes from underground
Timeseries, Stocks and Altair
Predicting Onset/Diagnosis of Chronic Conditions, Diabetes