Heather Grebe

Senior Data Scientist at Daupler
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Contact Information
us****@****om
(386) 825-5501
Location
United States, US
Languages
  • English -
Skills

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Bio

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Credentials

  • Machine Learning Engineering for Production (MLOps)
    Coursera
    Jan, 2022
    - Nov, 2024

Experience

  • Daupler
    • United States
    • Utilities
    • 1 - 100 Employee
    • Senior Data Scientist
      • Feb 2021 - Present

  • The Hartford
    • United States
    • Financial Services
    • 700 & Above Employee
    • Data Scientist
      • Mar 2019 - Jan 2021

    • Associate Data Scientist
      • Aug 2017 - Mar 2019

    • Data Science Intern
      • May 2017 - Aug 2017

  • HCA Healthcare
    • United States
    • Hospitals and Health Care
    • 700 & Above Employee
    • Clinical Informatics CDM Intern (Data Science Team)
      • Aug 2016 - Jan 2017

  • Middle Tennessee State University (MTSU)
    • United States
    • Higher Education
    • 700 & Above Employee
    • FOCUS Act Transition Team Member
      • Mar 2016 - Dec 2016

    • Graduate Research Assistant
      • Sep 2015 - Nov 2016

  • Wayne State University
    • United States
    • Higher Education
    • 700 & Above Employee
    • Research Assistant (Neutrino Physics)
      • May 2013 - Jan 2014

      Experimental particle physics Experimental particle physics

  • Department of Nuclear Physics CEU 2013
    • Newport News, VA
    • CEU Presenter
      • Oct 2013 - Oct 2013

      Title: Model independent extraction of the axial mass parameter in CCQE anti neutrino-nucleon scattering Abstract: Neutrino oscillation studies depend on a consistent value for the axial mass. For this reason, a model-independent extraction of this parameter from quasielastic (anti)neutrino-nucleon scattering data is vital. While most studies employ a model-dependent extraction using the dipole model of the axial form factor, we present a model-independent description using the z expansion of the axial form factor. Quasielastic antineutrino scattering data on C-12 from the MiniBooNE experiment are analyzed using this model-independent description. The value found, 〖0.85〗_(-0.06)^(+0.13)±0.13 GeV differs significantly from the value utilized by the MiniBooNE Collaboration, mA = 1.35 GeV. Show less

Education

  • Johns Hopkins Whiting School of Engineering
    Master of Science - MS, Computer Science
    2020 -
  • Middle Tennessee State University
    Master of Science (M.S.), Biostatistics
    2015 - 2017
  • Middle Tennessee State University
    Bachelor of Science (B.S.), Applied Physics
    2011 - 2015

Community

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