• 10 years experience building Predictive Models to drive company profitability and growth. These include models for Commercial Auto Pricing, General Liability Pricing, Real Estate Prospecting, HR Attrition. • Actively involved in communication and presentation of data science results and insights to our various stakeholders including senior management, underwriters, actuaries, and IT for implementation. • Excellent Communication and Presentation Skills, Problem-Solving, and Critical Thinking. • High Ethics and Integrity• Strong R and SAS programmer. (SAS certified). SQL • Python is my secondary language: Pandas, Sklearn, NLTK • Data Visualization: R's ggplot2, Spotfire • Web Apps: RShiny • Machine Learning: Regression (Linear/GLM,Logistic/Lasso), Gradient Boosting, Random Forest, Decision Tree, PCA, K-means clustering, Hierarchical clustering• Big Data: Spark in R using SparklyR, Data.Table (dtplyr) • Statistics: A/B Testing, Probability, Inference• Lifelong learner who actively seeks to learn the most cutting edge modeling techniques and software.• Completed the following career tracks on Datacamp: "Data Scientist with R Track", "Programming with R Track". CAS Actuarial Exams passed: P,FM,LC/ST,MFE,COther Skills:R, RStudio, RShiny, SQL, Tidyverse, ggplot2, dplyr, Exploratory Analysis, Data Visualization, Human Analytics (HR), Data Cleaning, Missing Data handling, Dates and Times, Functions, Importing Data, Cleaning Data, Sentiment Analysis, Text Mining - Bag of Words, Network Data, Anomaly Detection, Statistics, Data Mining, Machine Learning, SQL, A/B Testing, Multiple Regression, Logistic Regression, Machine Learning, GLMNet, Random Forest, Gradient Boosting, Data Science for Managers, Unsupervised Learning, kmeans clustering, hierarchical clustering, pca, Big Data with Spark in R with SparklyR, Big Data in memory with DataTable (dtplyr)