Madeline Hawkins

Senior Data Scientist at Brighterion, a Mastercard Company
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Contact Information
us****@****om
(386) 825-5501
Location
San Francisco Bay Area

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Credentials

  • Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
    Coursera
    Dec, 2019
    - Nov, 2024
  • Structuring Machine Learning Projects
    Coursera
    Dec, 2019
    - Nov, 2024
  • Neural Networks and Deep Learning
    Coursera
    Aug, 2019
    - Nov, 2024
  • C++ Certification
    Orange Coast College

Experience

    • United States
    • Software Development
    • 1 - 100 Employee
    • Senior Data Scientist
      • Mar 2021 - Present

    • Data Scientist II
      • Feb 2019 - Mar 2021

    • United States
    • Medical Equipment Manufacturing
    • 700 & Above Employee
    • Software Engineer Intern
      • Jun 2018 - Jan 2019

      Drove the management and reengineered unstructured data to validated structured data of 24000 subjects using Python and PySpark with Databricks Unified Analytics Platform. Ran exploratory analytics using Jupyter Notebooks and Pandas on patient data and found trends that answered questions on improvements for the product. Pioneered cross-functionality on deep learning project using image processing to identify vertebrae in x-rays. Drove the management and reengineered unstructured data to validated structured data of 24000 subjects using Python and PySpark with Databricks Unified Analytics Platform. Ran exploratory analytics using Jupyter Notebooks and Pandas on patient data and found trends that answered questions on improvements for the product. Pioneered cross-functionality on deep learning project using image processing to identify vertebrae in x-rays.

    • Undergraduate Research Assistant
      • Nov 2017 - Jun 2018

      Conducted machine learning research for Computational Genomics Lab. Collaborated model evaluation and exploration in Python and PyTorch to train models for variant identification. Sped preprocessing up to 3 times compared to traditional methods for large genomic data by utilizing parallelization techniques to create images for the model. Conducted machine learning research for Computational Genomics Lab. Collaborated model evaluation and exploration in Python and PyTorch to train models for variant identification. Sped preprocessing up to 3 times compared to traditional methods for large genomic data by utilizing parallelization techniques to create images for the model.

Education

  • University of California, Santa Cruz
    Bachelor’s Degree, Computer Science with Honors
    2016 - 2018
  • Orange Coast College
    Associate’s Degree, Mathematics
    2012 - 2016

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