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Statistical Modeler

Resume posted by aidenjohnson in Scientific.
Desired salary: $80,000.00
Desired position type: Any
Location: Hartford Connecticut, United States

Contact aidenjohnson

Summary

Data, Stats, R.

Education

Montana State University, Land Resources & Environmental Sciences Dept.

 General Responsibilities

  • Developed analysis methods and wrote code to answer relevant scientific questions for the laboratory.
  • Performed writing, editing, and data analysis for manuscript publication.
  • Applied for grants and fellowships relevant to research interests.
  • Collected organized, and analyzed multisource digital data.

Research

  • Thesis:“Scaling and Uncertainty in Landsat Remote Sensing of Biophysical Attributes.”
  • Applied a Random Forest classification to multi-source environmental data in R.
  • Implemented a multi-resolution wavelets change detection analysis in R and Matlab.
  • Completed an uncertainty analysis of remote sensing data via a Monte Carlo simulation in R and Matlab.

M.S. Land Resources & Environmental Sciences

Graduate Certificate in Applied Statistics

B.S. Forest Resource Management & GIS

Experience

Experience

 

Statistical Modeler                                                                        August 2014 – Present

State of Montana, Department of Revenue

  • Provide technical expertise for appraisal programs by developing, specifying and calibrating multivariate regression models for mass appraisal of residential and commercial properties to assist in determining market value for assessment of property taxes.
  • Perform special projects to inform statistical model development and data segmentation. Study methods include; creating interpolated surfaces using inverse distance weighting and kriging, applying clustering methods such as k-means, Principle Component Analysis.
  • Develop data visualization and reports for special projects.

 

Geospatial Data Editor                                                             June 2014 – August 2014

Energy Research Institute, Big Sky Carbon Sequestration Partnership      

  • Implemented linear regression model for improved estimates of carbon sequestration capacity in oil & gas wells.
  • Updated web map displays of storage estimates and static dataset for map display.

 

Graduate Research Assistant                                                        June 2011 – July 2014

Montana State University, Land Resources & Environmental Sciences Dept.

 General Responsibilities

  • Developed analysis methods and wrote code to answer relevant scientific questions for the laboratory.
  • Performed writing, editing, and data analysis for manuscript publication.
  • Applied for grants and fellowships relevant to research interests.
  • Collected organized, and analyzed multisource digital data.

Research

  • Thesis:“Scaling and Uncertainty in Landsat Remote Sensing of Biophysical Attributes.”
  • Applied a Random Forest classification to multi-source environmental data in R.
  • Implemented a multi-resolution wavelets change detection analysis in R and Matlab.
  • Completed an uncertainty analysis of remote sensing data via a Monte Carlo simulation in R and Matlab.

 

 

Course Instructor- Geographic Information Systems                     Fall Semester 2013

University of Montana-Western 

  • Developed and designed all course materials, lectures, lab exercises, and assignments for use in ArcGIS and R.

 

 

 

Graduate Teaching Assistant                                                        Jan. 2012 – May 2014

Courses: Environmental Biophysics, Remote Sensing & Digital Image Processing, Introduction to Soils, and Watershed Hydrology

Montana State University, Land Resources & Environmental Sciences Dept.  

  • Provided one-on-one lab help for project design, analysis methods, code writing, and R and Matlab debugging.
  • Designed, tested, and implemented a teaching methods experiment.

 

 

Remote Sensing Analyst                                                               June 2010 – May 2011

Red Castle Resources, Inc

  • Data acquisition and implementation of vegetation change detection SVM algorithm; drafted associated documentation and performed accuracy assessments on results.
  • Developed and presented a cohort of remote sensing courses for resource managers.
  • Provided geospatial analysis project development support to USDA Forest Service employees.
  • Researched and published a manual for carbon stock accounting via remote sensing methods.

 

Remote Sensing Analyst                                                               Dec. 2008 – May 2010

USDA Forest Service, Northern Regional Office, Engineering    

  • Processed remotely sensed imagery for use in a major vegetation-mapping project.
  • Address and resolve problems with data acquisition, processing techniques and product accuracy.
  • Classified remote sensing data using Random Forests in R, object oriented unsupervised classification in eCognition, and k-NN supervised classification in R.
  • Completed a comparative analysis of classification techniques accuracy in classifying land class and forest species data.

 

Non-commissioned Officer-Respiratory Specialist                         July 2002 – July 2010

U.S. Army Reserve, 4225th US Army Hospital

Skills

  • Computer Skills
  • • Microsoft Office Suite (Access, Word, Excel, Powerpoint), ESRI (ArcGIS, ArcInfo ArcMap, ArcView, ArcEditor, ArcReader), Erdas Imagine, R, Rstudio, R Markup, Matlab, SAS EPG, SQL, ORION CAMA.
  • Statistical Skills
  • • Algorithms, Diagnosis of Correlation structures, Optimization, Maximum Likelihood Estimation, Monte Carlo Analysis, Bayesian Statistics, Metropolis algorithm for high dimensional problems, Jacknife cross validation, finite difference analysis
  • • Graphical display and interpretation of multivariate data
  • • Regression: Non-linear, multiple, logistic, ANOVA
  • • Multivariate Analysis: Principle Component Analysis, Multidimensional Scaling, Exploratory and Confirmatory Factor Analysis, Cluster Analysis, Discriminant Analysis, Classification and Regression Trees, Distance based analysis techniques
  • • Sampling; Random, Stratified, Stratified Random, Cluster, Non-response, and Sampling Error
  • • Autoregressive models
  • • Interpolation, contouring, kriging, variograms
  • Personal Skills
  • • Excellent communication skills, leadership experience, team and community oriented, highly motivated and optimistic.