Pamela Nguyen

I'm a

About

This is a personal website I created using a bootstrap template to highlight my skills, interests and projects. My website is hosted on AWS and github pages. Please contact me if you would like to connect. :)

Data Analyst & Researcher.

My name is Pamela Nguyen and I have recently completed a Bachelor of Science in Computational Physics and Mathematics with a certificate in Elements of Computing and Scientific Computation & Data Sciences at the University of Texas at Austin. I am currently seeking internships and full time opportunities. My interests include: Data Analysis, Machine Learning, and Quantitative Research. Hook em'

  • Website: pamhacks.com
  • City: Austin, TX
  • Looking for: Full Time opportunities
  • Degree: Bachelor of Science
  • Email: pamela.c.nguyen@gmail.com

Here is my current resume and CV.

Resume

Summary

Pamela Nguyen

Inquisitive and data hungry researcher interested in data analysis and machine learning with 4+ years of experience.

  • Austin, TX
  • pamela.c.nguyen@gmail.com
  • Interests: Data Analysis, Machine Learning, Quantitative Research, Photography, Law: Intellectual Property & Business.

Education

Bachelor of Science in Computational Physics & Mathematics

2019-2022

University of Texas at Austin, Austin, TX

  • Certificate in Elements of Computing, Scientific Computation & Data Sciences

Skills

Programming Languages

  • Python (NumPy, pandas, scikit-learn, matplotlib, PyTorch, SymPy, SciPy)
  • C++
  • Java
  • Fortran 90

Tools and Platforms

  • Jupyter Notebooks
  • Bash/Unix/Linux
  • MATLAB
  • LaTex
  • Google Cloud Platforms
  • Git

Databases

  • SQL
  • Postgres
  • BigQuery
  • NoSQL
  • MongoDB
  • NoSQL
  • Excel

Languages

  • Spanish (A1)
  • French (A2)
  • English (Native)
  • Vietnamese (Social)

Professional Experience

Sales Specialist

June 2022 - Present

Apple, Austin, TX

  • Educate customers on Apple devices such as iPhone, iPad, Apple Watch, Mac, and software such as iOS and MacOS through interactive product test-runs and demonstrations
  • Collaborate with leads, technical experts, operations experts and coaches to deliver a seamless experience for customers
  • Guide customers through personal device set-up features such as Apple Wallet, Face ID/Touch ID, and Accessibility display troubleshoot information transfer through iCloud backup, Apple, and Android devices

Computer Science & Mathematics Instructor

May 2022 - Present

Juni Learning, Remote

  • Execute advanced computer science lesson plans including basic data structures, object-oriented programming, and machine learning algorithms over Zoom for students ages 8-18 while adapting to student needs and interests. Skills used: Python: Keras, NumPy, SciPy, Scikit-Learn, Java, C++, Scratch
  • Communicate with family members on a regular basis, providing updates and maintaining records on student progress and results from learning assessments.

Undergraduate Researcher & Data Analyst

Jan 2019 - Dec 2023

UT Austin (Molecular Biosciences), Austin, TX

  • Generated and executed computational pipelines using Python (pandas, NumPy, seaborn, matplotlib), Bash, and R for parsing, visualization, statistical analysis, and other processing of data generated by NGS workflows.
  • Implemented and maintained a GCP server and TACC project to upload TBs of C. elegans data and analyze data. Used by all members of the lab.
  • Produced and tested bash pipelines that converted raw sequencing data (FASTQ, FASTA) to binaries (BAM) in order to save storage and create readable variant data (VCF) for analysis. This pipeline was used to convert all sequencing data in the lab.
  • Improved the efficiency (-20 mins per 1TB of data) and the accuracy (+8%) of the sequencing pipelines by generating test data, adjusting pipeline parameters, and increasing CPU/RAM.
  • Consistently communicates with peers, professors, and researchers on implementing modern research tactics and improving accuracy of results and data

Technical Advisor

Mar 2020 - Jan 2021

Apple, Austin, TX

  • Operated and troubleshooted iOS and MacOS devices while remaining up-to-date with the latest technologies and solutions applicable to company products.
  • Consistently exuded professionalism and maintained privacy when handling customer information while sustaining standard average handle time and customer satisfaction.

Undergraduate Researcher & Data Analyst

June 2019 - Aug 2019

UT Austin (Astronomy), Austin, TX

  • Implemented and created Jupyter Notebooks using Python and libraries such as NumPy, Scipy, Sympy and PyTorch to analyze and simulate white dwarf stars data. Such tasks included the creation and calibration of dark and flat frames to calculate aperture photometry.
  • Obtained flat and dark data from the McDonald Observatory with given possible white dwarf star coordinates. Acquired over 4 days worth of data. Skills used: Python: NumPy, SciPy, Sympy, PyTorch

Projects

Data Analysis

Senior Research Thesis

Filtered, sorted, plotted and correlated the effects of rDNA copy number extremities on gene expression and genomic variation of over a million C. elegans records provided by the Million Mutation project. Used: Python: pandas, matplotlib, NumPy, seaborn

Infectious Disease Simulation

Model and tracked disease propagation within a population from an infectious person statistically using an explicit SIR model in C++. Used: C++, bash, Frontera (TACC), Matlab

Ensemble Classifiers Analysis on Credit Card Transactions

Partitioned the data for cross validation using a stratified k-fold and fitted scikit-learn machine learning algorithms: AdaBoost and Random Forests, on over 140,000+ credit card transactions to predict fraudulent charges. Used: Python: scikit-learn, matplotlib

Hierarchical Clustering on Raw Ballots Casts from Presidential Candidates

Implemented Scipy hierarchical clustering functions to plot dendrograms using various proximity measures: ward, min, and max, on data provided by The American Presidency Project to calculate their Cophenetic Correlation Coefficient (CPCC). Used: Python: scikit-learn, Sci-Py

RDBMS Hardware and Software Optimizations

Deployed, tested, and improved the runtime of a relational database management system (RDBMS) environment on a Compute Engine instance in GCP using Postgres 13. Used: Postgres, Python, GCP, Git, bash

Algorithm Optimizations

GNU and Intel C++ Compiler Optimizations

Experimented, researched, and sped up a C++ file using compiler transformations on both Intel (icc) and GNU (g++) compilers on the Texas Advanced Computing Center (TACC) Frontera nodes. Used: C++, bash, Frontera (TACC), Matlab

Comparison of Numerical Solvers for Nonlinear Equations

Developed C++ scripts to use the numerical methods: fixed point iteration, Newton-Raphson method, secant method, and Newton-bisection method to find the maximum deflection point of a loaded bookshelf given the Young’s modulus. Used: Matlab, C++, Excel

Clustering Algorithms Analysis

Partitioned the data for cross validation using a stratified k-fold and fitted scikit-learn machine learning algorithms: AdaBoost and Random Forests, on over 140,000+ credit card transactions to predict fraudulent charges. Used: Python: scikit-learn, matplotlib