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Data Scientist Resume

3.00 Rating

MA

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).

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