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Research Assistant Resume

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Madison, WI

PROFILE:

  • Recent Physics PhD graduate with background in scientific programming and actuarial analysis.
  • Has experience processing and analyzing data, then telling stories with it using visualizations.
  • Used a sample of Enron employee data to build a machine learning model that identifies potential frauds.
  • Utilized PCA for feature selection and Stratified - Shuffled Cross Validation for parameter tuning and model assessment. Coded in Python.
  • MATLAB software that processes raw MRI data for conversion into images. Includes anatomical images and verification that my calibration method works.
  • Wrote code in R to acquire high school graduation rate data from the web, process it, and generate an interactive color map.

DATA ANALYTICS SKILLS:

Languages: Python numpy; pandas; scikit-learn, R with Markdown, C/C++, MATLAB, C-Shell, SQL

Machine Learning Concepts : Bias-Variance Tradeoff, Linear & Logistic Regression, KNN, K-Means, LDA, QDA, Decision Trees, Random Forest, Bootstrap, Cross-Validation, PCA, SVM

Software Development Tools: Anaconda, Spyder, Jupyter Notebooks, Git Version Control

Visualization Tools: Matplotlib, Leaflet for R, ggplot2, maptools, Tableau (exposure)

WORK EXPERIENCE:

Research Assistant

Confidential, Madison, WI

Responsibilities:

  • Reduced primary source of image blur by utilizing simulations to improve data collection method.
  • In imaging terminology, image energy retention increased from 50% to 90% (MATLAB, C)
  • Made MRI scanning possible with 3D rosette-like data collection scheme by developing a memory efficient implementation that utilizes matrix multiplication (C)
  • Enabled the 3D rosette-like method with capability to scan the human brain, breasts, hip joint, and knee joint by implementing three distinct tissue contrast mechanisms (C)
  • Eliminated secondary blurring and “grey haze” artifact in final images by devising a calibration method to correct MRI data errors (MATLAB, C)
  • Presented research findings at international conferences and workshops in Sweden, Italy, Canada, US

Actuarial Analyst

Confidential, San Francisco, CA

Responsibilities:

  • Valued pension plans for accounting disclosures and government funding requirements
  • Reduced annual data project time by 20% by automating manual steps of data process (Visual Basic)
  • Saved client 25% in cash contributions by resolving data issues (Visual Basic)
  • Proved that office’s 3 rd largest client complied with non-discrimination requirements (Fortran 88)

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