cv

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Basics

Name William D'Arcy Kenworthy
Label Quantitative Researcher
Email darcy-at-darcykenworthy.com
Phone +1 (704) 497-7230
Url https://darcykenworthy.github.io
Summary PhD-trained data scientist with expertise in statistical modeling, large-scale data analysis, and systematic uncertainty correction. Experience developing analytical frameworks adopted across international research collaborations. Seeking to leverage my expertise in statistical modeling towards market analysis and risk assessment.

Work

  • 2022.01 - Present
    Postdoctoral Researcher
    Oskar Klein Center, Stockholm University
    Advisor: Ariel Goobar
    • Worked on the Zwicky Transient Facility, release of largest-to-date sample of cosmological supernovae
    • Analyzed large datasets using statistical models to extract systematic patterns and correct for measurement biases
    • Developed and validated predictive models for time-series data with sub-percent precision requirements
    • Collaborated with international teams on data processing pipelines and uncertainty propagation methods
  • 2017.01 - 2022.01
    Graduate Research Assistant
    Johns Hopkins University
    Advisor: Adam Riess (Nobel Laureate)
    • Worked on measurement of the Hubble constant and dark energy using Type Ia supernovae
    • Developed SALT3 statistical modeling framework for analyzing observational time-series data
    • Created methods for systematic bias identification and correction in large-scale measurement campaigns
    • Implemented Bayesian statistical models for parameter estimation with highly correlated uncertainties

Education

  • 2017.01 - 2019.01

    Baltimore, MD, USA

    Masters of Art
    Johns Hopkins University
    Physics and Astronomy
  • 2017.01 - 2022.01

    Baltimore, MD, USA

    PhD
    Johns Hopkins University
    Astronomy
  • 2016.01 - 2017.01

    Cambridge, UK

    Masters of Science
    University of Cambridge
    Part III Astrophysics
  • 2013.01 - 2017.01

    Cambridge, UK

    Baccalaureate of Arts
    University of Cambridge
    Part I Natural Sciences, Part II Physics

Publications

Skills

Programming
Python (data analysis, photometry)
Stan (statistical modeling)
JAX/Equinox (high-speed computation)
Data Analysis
Large-scale dataset processing
Statistical modeling
Uncertainty quantification
Systematic bias correction
Model validation
Side Projects
Swift
Julia
ML
Modeling
Time series analysis
Bayesian statistics
Simulation-based inference
Tooling
AWS
Git
Mercurial