Resume

Machine learning engineer with a diverse background in semiconductor manufacturing. Aim to use my expertise in data mining and machine learning to improve products and processes. Over 3 years of experience developing production level software and data mining with Python and R.

Education

• M.S. Data Science, Southern Methodist University, Dec. 2020, Outstanding Graduate Award
• B.S. Engineering Physics, LeTourneau University, 2013, Magna Cum Laude
• B.S. Electrical Engineering, LeTourneau University, 2013, Magna Cum Laude

Certifications

• TensorFlow in Practice; 2020; Coursera-DeepLearning.AI (View Certificate)
• Data Analyst Nanodegree; 2018; Udacity (View Certificate)
• Divide & Conquer, Sorting, & Randomized Algorithms; 2017; Coursera-Stanford (View Certificate)

Work Experience

• Machine Learning Engineer at State Farm (2/2021 - Present)
  • GitLab CI/CD pipelines
  • Flask/FastAPI web API development for model service calls
  • Containers-as-a-Service (CaaS) deployments
  • Docker image development
• Test Engineer (Software Development) at Texas Instruments Inc. (2/2014 - 2/2021)
  • Reduced tuning time of manufactured devices with a kNN model, reducing tuning time by 10%.
  • Removed redundant manufacturing tests based on regression analysis, improving manufacturing test time by 10%.
  • Headed the development of code libraries, eliminating 90% critical bug occurrences and decreasing program development time by 20%. The team included engineers from TI-Dallas and TI-Germany.
  • Extracted, transformed, and analyzed large volumes data to ensure quality of production test programs, identify yield issues, and validate test methods.
  • Provided analyses to management for project updates and project status reviews. Communicated insights from data analysis to stakeholders through team presentations and reports.
  • Created development operations (DevOps) tools to simplify development and deployment of test programs. Scripts were developed in Python and executed steps such as compiling production program builds, auto-tagging program releases, and pushing new program releases out to servers.
  • Collaborated with global teams (design, manufacturing, applications, marketing, etc.) to clarify goals, solve test functionality problems, quality issues, and support on-time arrival of deliverables to stakeholders.
  • Utilized git for version control for software development.

Technical Skills

• Data Science: data cleaning and preparation, exploratory data analysis, visualization, communicating insights, regression analysis, ANOVA, hypothesis testing
• Machine Learning: linear and non-linear modeling, model interpretation, model selection, feature importance, feature reduction, deep learning, clustering
• Software Development: test driven development, library/package development and deployment (at production)
• Tools: Linux, git, bash, Jupyter

Personal Skills and Qualities

• Strong written and verbal communication capabilities
• Strong team player
• Self-starter
• Adaptable to changing priorities
• Passionate about continuous learning
• “Make it Happen” attitude

Programming Languages

• Python
  • Data Science packages: NumPy, SciPy, Scikit Learn (sklearn), Pandas, Jupyter, Gensim, SpaCy
  • Deep Learning packages: TensorFlow, Keras
  • Package and API design
  • Unit testing
• R
  • The tidyverse ecosystem: ggplot2, dplyr, caret
  • Unit testing

Publications

Multi-Modal Classification Using Images and Text

Miller, Stuart J.; Howard, Justin; Adams, Paul; Schwan, Mel; and Slater, Robert (2020) "Multi-Modal Classification Using Images and Text," SMU Data Science Review: Vol. 3 : No. 3, Article 6.

Service and leadership

• ODSC West Volunteer (2019)

Honors

• Outstanding Graduate Award, Southern Methodist University, 2020
• Alpha Chi National Honor Society, Southern Methodist University, 2019-2020
• Epsilon Eta Sigma, Engineering Honor Society, LeTourneau University, 2013
• President’s List and Dean’s List, LeTourneau University, 2009-2013
• Eagle Scout, Boy Scouts of America, 2008