Curriculum Vitae

Mark Hagemann, Ph.D. Link to heading

Data Scientist, Engineer

Education Link to heading

University of Massachusetts Link to heading

  • Ph.D. in Civil and Environmental Engineering 2016
    • Dissertation: Predictive modeling of riverine constituent concentrations and loads using historic and imposed hydrologic conditions
  • M.S. in Statistics 2017

Carleton College Link to heading

  • B.A. in Geology 2010

Work Experience Link to heading

EAB Global Link to heading

  • Senior Data Scientist (Nov 2019 - Apr 2024)
    • Developed and maintained lead-scoring machine learning models on R / AWS infrastructure, improving AUC by 5-10 points for most models through feature engineering and hyperparameter tuning.
    • Created analytics dashboards using R, SQL, Shiny, and CSS to enhance data accessibility and decision-making.
    • Built and disseminated R packages to streamline data science workflows across teams.

Ohio State University Link to heading

  • Postdoctoral Researcher (Jan 2018 - Oct 2019)
    • Contributed to code development for validating error estimates and visualizing errors in statistical models for monitoring rivers using spaceborne radar.
    • Co-developed a model to quantify measurement uncertainty for a NASA satellite mission.

University of Massachusetts Link to heading

  • Postdoctoral Researcher (Sept 2016 - Dec 2016)
    • Designed and published a Bayesian method to estimate streamflow using satellite data.
    • Led instruction for undergraduate statistics courses and wrote open-source R packages.

University of Massachusetts Link to heading

  • Postdoctoral Researcher (July 2017 - Jan 2018)
    • Designed and published a Bayesian method to estimate streamflow using satellite data.
    • Led instruction for undergraduate statistics courses and wrote open-source R packages.

Carleton College Link to heading

  • Visiting Assistant Professor (Jan 2017 - Mar 2017)
    • Provided instruction for a 10-week hydrology course and laboratory.

Skills Link to heading

  • R
  • Python
  • Stan
  • MATLAB
  • Linux/Bash
  • SQL
  • Supervised and Unsupervised Learning
  • Regression
  • Classification
  • Bayesian Inference
  • Amazon Web Services
  • Data Cleaning
  • Feature Engineering
  • Statistical and Probabilistic Analysis
  • ggplot2
  • Shiny Dashboard
  • htmlwidgets
  • plotly.js
  • R package development
  • Reproducible Research
  • Git/Github
  • Google Cloud Platform
  • Docker
  • Machine Learning
  • Mathematical Statistics
  • Bayesian Statistics
  • Linear Models
  • Regression Modeling
  • Time Series Analysis
  • GIS Analysis

Projects Link to heading

Real-Time Categorization Tool for Online Listening Sessions Link to heading

  • Developed a tool using the LangChain framework for real-time categorization of responses during online listening sessions. Integrated AI components in Python and built a user interface using R/Shiny.
  • Technologies: LangChain, Python, R, Shiny

Personal Project: LLM-based AI Chat Interface in Rmarkdown (“Larkdown”) Link to heading

  • Created a bilingual project using R and Python to develop a chat interface with LLMs within Rmarkdown documents for interactive AI interactions.
  • Technologies: R, Python
  • Link: Larkdown

Leadership Link to heading

  • Co-Chair of Programming, Graduate Researchers in Data (GRiD) — UMass Amherst, June 2015 - May 2016
  • Student Co-Chair, New England Graduate Student Water Symposium — UMass Amherst, Sept. 2015

Honors and Awards Link to heading

  • National Water Center Innovators Program, 2016 Consortium of Universities for the Advancement of Hydrologic Science, Inc.
  • R.A. Noga and K.M. Noga Fellowship, 2015 UMass Civil and Environmental Engineering
  • Phi Beta Kappa, 2010 Beta chapter of Minnesota
  • Distinction in senior thesis, 2010 Carleton College Geology
  • Eagle Scout, 2006
  • National Merit Finalist