Jeff Mohl

Director, Research and Analytics at American Medical Group Association (AMGA)
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Contact Information
us****@****om
(386) 825-5501
Location
Bozeman, Montana, United States, US

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Experience

    • United States
    • Hospitals and Health Care
    • 1 - 100 Employee
    • Director, Research and Analytics
      • Nov 2021 - Present

      • Lead a team of four research analysts to produce impactful health services research and provide analytic support to AMGA population health initiatives. • Leverage large scale, real-world databases of electronic medical record and adjudicated claims data to generate insights relevant to pressing public health questions, with a focus on chronic disease and value based care • Design, implement, and publish quantitative and qualitative research studies in collaboration with academic and… Show more • Lead a team of four research analysts to produce impactful health services research and provide analytic support to AMGA population health initiatives. • Leverage large scale, real-world databases of electronic medical record and adjudicated claims data to generate insights relevant to pressing public health questions, with a focus on chronic disease and value based care • Design, implement, and publish quantitative and qualitative research studies in collaboration with academic and industry partners • Support AMGA's national public health campaigns and group learning collaboratives through quality measure development, monitoring, and evaluation

    • Senior Population Health Research Analyst
      • Nov 2020 - Nov 2021

      • Leveraged machine learning techniques to develop predictive models to identify high risk patients, and classification models to improve the quality of our data resource (https://doi.org/10.1002/acr.25013) • Lead the development, design, implementation, and dissemination of research projects with academic and industry partners • Provided subject matter expertise in machine learning, statistical analysis, and quantitative research design to a diverse range of health services research… Show more • Leveraged machine learning techniques to develop predictive models to identify high risk patients, and classification models to improve the quality of our data resource (https://doi.org/10.1002/acr.25013) • Lead the development, design, implementation, and dissemination of research projects with academic and industry partners • Provided subject matter expertise in machine learning, statistical analysis, and quantitative research design to a diverse range of health services research projects

    • United States
    • Higher Education
    • 700 & Above Employee
    • Postdoctoral Research Associate
      • May 2020 - Nov 2020

      Durham, North Carolina, United States • Analyzing neural and behavioral data using statistical methods (inferential and descriptive) and computational modeling • Data visualization and communication in papers and presentations • Development of custom data analysis pipelines in MATLAB and R

    • Graduate Research Assistant
      • Aug 2014 - May 2020

      Raleigh-Durham, North Carolina Area Computational models of human and primate behavior to evaluate perceptual strategies across species • Designed, piloted, and carried out a novel behavioral experiment to investigate how visual and auditory information is combined to produce optimal multisensory judgements • Developed a range of custom mathematical models of behavior in Matlab, and conducted a model comparison to quantitatively describe behavior across multiple subjects and species… Show more Computational models of human and primate behavior to evaluate perceptual strategies across species • Designed, piloted, and carried out a novel behavioral experiment to investigate how visual and auditory information is combined to produce optimal multisensory judgements • Developed a range of custom mathematical models of behavior in Matlab, and conducted a model comparison to quantitatively describe behavior across multiple subjects and species (https://github.com/jmohl/CI_behavioral) • Discovered that primates use an approximate Bayesian strategy to compare auditory and visual stimuli Statistical modeling of rapidly fluctuating neural time-series data • Collaborated with members of the statistical science department to develop a novel analysis strategy for time varying neural signals, now released (https://github.com/tokdarstat/Neural-Multiplexing) and available to the scientific community. • Designed and implemented a series of computational tests to evaluate reliability and robustness of statistical method (https://arxiv.org/abs/2001.11582) • Interfaced with labs across four universities to implement analysis on diverse datasets

    • United States
    • Software Development
    • 100 - 200 Employee
    • Software Developer
      • May 2013 - Aug 2013

      • Updated and improved internal website and database framework through the modification of existing code and the introduction of new tools • Provided support, technical consulting, and bug resolution to internal sales staff • Gained a working competency in multiple programming languages (Visual Basic, Java, C, and SQL) and enterprise coding fundamentals under the mentorship of a senior developer

    • United States
    • Aviation & Aerospace
    • 700 & Above Employee
    • Mechanical Engineering Intern
      • Jun 2012 - Aug 2012

      • Designed interior ceiling configurations to satisfy customer specifications under supply chain and manufacturing constraints

Education

  • Duke University
    Doctor of Philosophy (Ph.D.), Neurobiology and Neurosciences
    2014 - 2020
  • Montana State University-Bozeman
    Bs, Mechanical Engineering
    2009 - 2014

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