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Logan Thomas

Data Scientist & Software Engineer
loganthomas.dev | logan.thomas005@gmail.com | 321.961.9107

Summary of Qualifications

I am a highly-motivated and naturally curious individual with experience using Python, Spark, SQL, and Data Science/Machine Learning techniques. I exhibit an analytical and detail-oriented nature, while placing strong value on building relationships.

Skills

  • Programming Language – Python, SQL, Spark, BigQuery (Google Cloud Platform)
  • Methodology – Data Munging, Data Mining, Machine Learning, Scripting, Automation, Web Development
  • Data Visualization – Matplotlib, Plotly, Spotfire, Tableau
  • Data Science Advisor – Individual mentorship & advisement

Talks & Tutorials

Education

University of Florida, Gainesville, FL
Master of Science Mechanical Engineering (Minor in Statistics)
May 2014

Palm Beach Atlantic University, West Palm Beach, FL
Bachelor of Science Mathematics (Minor in Biblical Studies)
Summa Cum Laude May 2012

Experience

Fullstroy, Austin, TX (Remote)
Senior Data Science Software Engineer
March 2025 - Present

  • Design and execute experiments that develop algorithms and models that are actionable and create meaningful business value
  • Develop machine learning systems that model, classify and predict behavior
  • Write production-quality code and help design systems that incorporate these algorithms and models into product features and services
  • Set up instrumentation and analyses that continuously monitor product features for quality assurance and customer success
  • Collaborate with engineers to architect new data science product infrastructure

Pattern Bioscience, Austin, TX
Senior Data Scientist
December 2023 - March 2025

  • Utilized
machine
learning
algorithms
to
extract
and
identify
metabolic signatures
  • Led
ad
hoc
analyses
as
embedded
data
scientist
within
molecular
biologist team
  • Supported
data
engineering
processes
and
automation
efforts

SciPy Conference Tutorial Co-Chair, Austin, TX
January 2022 - January 2025

PyTexas Committee Member, Austin, TX
January 2023 - January 2024

Enthought, Austin, TX
Scientific Software Developer & Python Trainer
February 2021 - December 2023

  • Applied machine learning and deep learning expertise to consulting projects
  • Taught machine learning, deep learning, and Python focused courses
  • Solved technical problems through efficient, idiomatic, and unit tested code

DataCamp, Remote
Data Science Course Instructor
February 2019 - October 2022

  • Designed interactive online course for data scientists focused on writing efficient Python code here
  • 4 hours of content (15 videos with 53 exercises)
  • 95,000+ course participants
  • 4.7 / 5 average course rating
  • Included in curriculum for:
    • Data Engineer with Python (Career Track)
    • Python Programmer (Career Track)
    • Python Programming (Skill Track)
    • Python Toolkit (Skill Track)

Protection Engineering Consultants, Austin, TX
Senior Associate Data Scientist
August 2019 - February 2021

  • Developed an evolutionary algorithm library for deploying multi-gene genetic programming and symbolic regression (DEAP and SymPy)
  • Enhanced computer vision algorithms for autonomous fragment tracking (OpenCV)
  • Led Python projects and promoted Git usage within the team
  • Security Clearance as of Sept 2020

Nielsen, Austin, TX
Machine Learning & Algorithms Team - Lead Data Scientist
October 2018 - August 2019

  • Developed and implemented machine learning models to drive data-driven insights
  • Identified patterns and anomalies in large datasets to optimize decision-making processes
  • Integrated diverse datasets to provide actionable insights for stakeholders
  • Promoted best practices including clean code, version control, and unit testing to ensure quality outcomes

Nielsen, Austin, TX
Machine Learning & Algorithms Team - Senior Data Scientist
July 2017 - October 2018

  • Launched state of the art automation engine leveraging network analysis, community clustering, maximum bipartite graph matching, and term frequency-inverse document frequency (TF-IDF)
  • Deployed automated data preparation pipeline and deep learning LSTM model using Databricks platform, AWS, TensorFlow, and Keras
  • Oversaw model development/evaluation for cookie classification techniques comparing XGBoost, AdaBoost, and other machine learning classifiers
  • Engineered end-to-end software solution for Total Ad Ratings product utilizing random forest models, k-d trees, and convex optimization
  • Developed R&D data analysis pipeline for viewer assignment project leveraging Databricks platform and Apache Spark

Columbia University School of Professional Studies, New York, NY
Applied Analytics in an Organizational Context - Course Facilitator Associate
September 2016 - December 2016

  • Facilitated lessons on Data Science, Open Source, and Modern Analytics (approximately 20 students)

Nielsen, San Francisco, CA
Digital Product Team - Senior Data Scientist
August 2016 - July 2017

  • Supported development/improvement of digital measurement products
  • Deployed methodological enhancements to foundational machine learning models: age correction model, cookie classification models, and invalid traffic techniques
  • Implemented Agile framework with App Dev and Engineering teams to create production level code

Nielsen, Tampa, FL & San Francisco, CA
Emerging Leaders Program - Data Science
July 2014 - August 2016

Rotation 4: Watch Product Enhancement Team (San Francisco, CA)
February 2016 - August 2016

  • Lead Analyst for Total Content Ratings (TCR) research leveraging new Data Matching System
  • Created, implemented, and enhanced code using SQL and R programming languages
  • Coordinated development of data quality assurance checks for implementation of TCR research
  • Authored two description of methodology papers that illustrate and annotate TCR enhancements

Rotation 3: Technology & Telecom Team (San Francisco, CA)
August 2015 - February 2016

  • Voiced unique opportunities available to Verizon from Nielsen’s diverse Telecom product line
  • Streamlined client communication procedures through self-developed technological updates
  • Developed comprehensive knowledge of Telecom databases through supporting Solutions & Analytics Team

Rotation 2: Audio Sample Acquisition Team (Tampa, FL)
January 2015 - August 2015

  • Documented sampling procedures across Nielsen product portfolio (Television, Audio, and Scarborough)
  • Led business wide analysis of sample de-duplication procedure
  • Presented list of key findings, best practices, and potential solution ideas to key stakeholders

Rotation 1: Behavioral Methods Team (Tampa, FL)
July 2014 - January 2015

  • Performed cost-analysis of TV Diary incentives resulting in $500,000 worth of savings
  • Led cross-functional team in evaluation of CATI logic within scripts used for phoning households
  • Developed informative FAQ website offered to respondents