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
What I've been reading.
Sat Links
Analyzing Size of Armed Forces From 1947 - 1963 with statsmodels
Friday Links
Analyzing US Real Interest Rate From 1959 - 2009 with statsmodels
Analyzing US Inflation From 1959 - 2009 with statsmodels
Analyzing US Unemployment From 1959 - 2009 with statsmodels
Stock Market and Optimal Portfolio Anaylsis scipy and quandl
Stock Market and Portfolio Anaylsis with pandas_datareader and quandl
NLP Heatmaps with Seaborn
NLP ngrams With Python
NLP with Pyspark
Clustering with Pyspark
Regression and Classification with Pyspark ML
Window functions and Pivot Tables with Pyspark