Data Scientist Resume MA - Hire IT People

SKILLS:

Statistical Packages: R, SAS, MATLAB, MS Excel, iPython, Jupyter, H2O

Visualization Packages: ggplot2, Shiny, Tableau Operating Systems Windows, Linux, Mac OSX

Databases: Microsoft SQL Server, Hadoop (Basic) Others GitHub, SourceTree, AmazonWebServices

Computer Languages: Python, C++, PowerShell, HTML, XML & C

RELEVANT WORK EXPERIENCE:

Data Scientist

Confidential, MA

Responsibilities:

Creating video tutorials of scripts for using R, RMarkdown, Jupyter and H2O with Amazon Web Services.
Creating slides for Spatial Analysis using R and updating the code using GitHub.

Data Scientist

Confidential, MA

Responsibilities:

Utilized count models, logistic regression and machine learning algorithms to meet client business needs.
Developed and implemented statistical tools to build predictive models helping support clients in customer marketing and demand generation initiatives;
Worked closely to productize the algorithms to address real world.
Collaborated with internal consulting teams to set analytic objectives, approach and work plans.
Wrote macros, performed analytics and automated statistical procedures utilizing SAS.

Big Data Scientist

Confidential, MA

Responsibilities:

Used regression models, K Nearest Neighbours algorithms & Kernel methods to solve the spot brokerage pricing.
Used statistical packages R, IPython for the implementation of the statistical algorithms.
Used Shiny for virtual demonstration and communicate with software engineering and business stakeholders.
Used gglplot2, googleVis and RCharts for the data visualization to communicate with peers and business users.
Wrote PowerShell scripts to validate our models by performing QA, UAT and automating database deployment.
Developed a distributed validation process using AWS platform and thus decreasing our run time from 32 to 1 hr.
Installed Hive using Ambari services in our Amazon Web Services instances; Deployed our database to decrease the deployment run time and wrote PowerShell scripts to automate the process.

Research Modelling/Graduate Research

Confidential, MA

Responsibilities:

Performed Confidential transformations and Principal Component Analysis on the Physical Features to minimize the non - normality and correlation of the dependent variables respectively.
Used data mining techniques like Artificial Neural Networks, Decision Trees and K means Clustering over the of 200 miles of Brockton road network to develop a Repair & Maintenance Strategy algorithm.
Developed regression and probabilistic predictive models using extreme weather (from NOAA database) and typical weather such as precipitation, temperature, freeze thaw cycles, etc. (from LTTP database).