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Language Skills

Typescript
R
Python
C++
Bash
SQL
AWK

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Made with my package datadrivencv.

The source code is available at https://github.com/nstrayer/cv.

Last updated on 2025-04-02.

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Nick Strayer

As a software developer I use my background in data science to build tools to help people explore, understand, and work with their data better. I have made visualizations viewed by hundreds of thousands of people, sped up query times for 25 terabytes of data by an average of 4,800 times, and built packages for R that let you do magic.

Education

PhD., Biostatistics

Vanderbilt University

Nashville, TN

2020

B.S., Mathematics, Statistics (minor C.S.)

University of Vermont

Burlington, VT

2015

  • Thesis: An agent based model of Diel Vertical Migration patterns of Mysis diluviana
  • Focused on computational efficiency, simulation optimization, and interactive model exploration

Research Experience

Graduate Research Assistant

TBILab (Yaomin Xu’s Lab)

Vanderbilt University

Current - 2015

  • Primarily working with large EHR and Biobank datasets.
  • Developing network-based methods to investigate and visualize clinically relevant patterns in data.

Data Science Researcher

Data Science Lab

Johns Hopkins University

2018 - 2017

  • Building R Shiny applications in the contexts of wearables and statistics education.
  • Work primarily done in R Shiny and Javascript (node and d3js).

Undergraduate Researcher

Rubenstein Ecosystems Science Laboratory

University of Vermont

2015 - 2013

  • Analyzed and visualized data for CATOS fish tracking project.
  • Head of data mining project to establish temporal trends in population densities of Mysis diluviana (Mysis).
  • Ran project to mathematically model the migration patterns of Mysis (honors thesis project.)

Human Computer Interaction Researcher

LabInTheWild (Reineke Lab)

University of Michigan

2015

  • Led development and implementation of interactive data visualizations to help users compare themselves to other demographics.

Undergraduate Researcher

Bentil Laboratory

University of Vermont

2014 - 2013

  • Developed mathematical model to predict the transport of sulfur through the environment with applications in waste cleanup.

Research Assistant

Adair Laboratory

University of Vermont

2013 - 2012

  • Independently analyzed and constructed statistical models for large data sets pertaining to carbon decomposition rates.

Industry Experience

While most recently I have had the job title of “software engineer”, I have worked in a variety of roles ranging from journalist to data scientist. Ultimately categorization is hard.

Principal Software Engineer

Posit

Remote

Current - 2024

  • Architect and develop full-stack solutions for the Positron data science IDE
  • Worked across the Typescript, Python, and Rust codebase to build user-centric interfaces that balance performance with intuitive design
  • Collaborate across teams to ensure reliable, maintainable codebase architecture
  • Mentored junior developers on frontend best practices and code quality standards

Senior Software Engineer

Posit

Remote

2024 - 2023

  • Created and led development of ShinyUiEditor, a React-based drag-and-drop interface builder
  • Designed architecture for real-time previewing and component manipulation using custom psuedo-ast format that allowed translation into either R or Python from the same ast.
  • Spearheaded work to simplift and unify the UI layer of R and Shiny using custom webcomponents.

Software Engineer

Posit

Remote

2023 - 2020

  • Part of team who created Shiny for Python, a ground-up rewrite of R’s Shiny framework in Python

Data Journalist - Graphics Department

New York Times

New York, New York

2016

  • Reporter with the graphics desk covering topics in science, politics, and sport.
  • Work primarily done in R, Javascript, and Adobe Illustrator.
  • Developed interactive, data-dense visualizations viewed by hundreds of thousands of users

Engineering Intern - User Experience

Dealer.com

Burlington, VT

2015

  • Built internal tool to help analyze and visualize user interaction with back-end products.

Data Science Intern

Dealer.com

Burlington, VT

2015

  • Worked with the product analytics team to help parse and visualize large stores of data to drive business decisions.

Data Artist In Residence

Conduce

Carpinteria, CA

2015 - 2014

  • Envisioned, prototyped and implemented visualization framework in the course of one month.
  • Constructed training protocol for bringing third parties up to speed with new protocol.

Software Engineering Intern

Conduce

Carpinteria, CA

2014

  • Incorporated d3.js to the company’s main software platform.




Teaching Experience

I am passionate about education. I believe that no topic is too complex if the teacher is empathetic and willing to think about new methods of approaching task.

Javascript for Shiny Users

RStudio::conf 2020

N/A

2020

Data Visualization Best Practices

DataCamp

N/A

2019

  • Designed from bottom up course to teach best practices for scientific visualizations.
  • Uses R and ggplot2.
  • In top 10% on platform by popularity.

Improving your visualization in Python

DataCamp

N/A

2019

  • Designed from bottom up course to teach advanced methods for enhancing visualization.
  • Uses python, matplotlib, and seaborn.

Advanced Statistical Learning and Inference

Vanderbilt Biostatistics Department

Nashville, TN

2018 - 2017

  • TA and lectured
  • Topics covered from penalized regression to boosted trees and neural networks
  • Highest level course offered in department

Advanced Statistical Computing

Vanderbilt Biostatistics Department

Nashville, TN

2018

  • TA and lectured
  • Covered modern statistical computing algorithms
  • 4th year PhD level class

Statistical Computing in R

Vanderbilt Biostatistics Department

Nashville, TN

2017

  • TA and lectured
  • Covered introduction to R language for statistics applications
  • Graduate level class

Selected Data Science Writing

I regularly blog about data science and visualization on my blog LiveFreeOrDichotomize.

Using AWK and R to Parse 25tb

LiveFreeOrDichotomize.com

N/A

2019

  • Achieved 4,800x performance improvement for large-scale genomic data processing.
  • Reached top of HackerNews multiple times

Classifying physical activity from smartphone data

RStudio Tensorflow Blog

N/A

2018

  • Walk through of training a convolutional neural network to achieve state of the art recognition of activities from accelerometer data.
  • Contracted article.

The United States of Seasons

LiveFreeOrDichotomize.com

N/A

2018

  • GIS analysis of weather data to find the most ‘seasonal’ locations in United States
  • Used Bayesian regression methods for smoothing sparse geospatial data.

A year as told by fitbit

LiveFreeOrDichotomize.com

N/A

2017

  • Analyzing a full years worth of second-level heart rate data from wearable device.
  • Demonstrated visualization-based inference for large data.

MCMC and the case of the spilled seeds

LiveFreeOrDichotomize.com

N/A

2017

  • Full Bayesian MCMC sampler running in your browser.
  • Coded from scratch in vanilla Javascript.

The Traveling Metallurgist

LiveFreeOrDichotomize.com

N/A

2017

  • Pure javascript implementation of traveling salesman solution using simulated annealing.
  • Allows reader to customize the number and location of cities to attempt to trick the algorithm.

Selected Press (About)

Great paper? Swipe right on the new ‘Tinder for preprints’ app

Science

N/A

2017

  • Story of the app Papr made with Jeff Leek and Lucy D’Agostino McGowan.

Swipe right for science: Papr app is ‘Tinder for preprints’

Nature News

N/A

2017

  • Second press article for app Papr.

The Deeper Story in the Data

University of Vermont Quarterly

N/A

2016

  • Story on my path post graduation and the power of narrative.



Selected Press (By)

The Great Student Migration

The New York Times

N/A

2016

  • Most shared NYT article of August 2016, demonstrating ability to create engaging UIs.
  • Used d3.js to realtime render 100 maps for personalized inspection for readers.

Wildfires are Getting Worse, The New York Times

The New York Times

N/A

2016

  • GIS analysis and modeling of fire patterns and trends
  • Data in collaboration with NASA and USGS

Who’s Speaking at the Democratic National Convention?

The New York Times

N/A

2016

  • Data scraped from CSPAN records to figure out who talked and past conventions.

Who’s Speaking at the Republican National Convention?

The New York Times

N/A

2016

  • Used same data scraping techniques as Who’s Speaking at the Democratic National Convention?

A Trail of Terror in Nice, Block by Block

The New York Times

N/A

2016

  • Led research effort to put together story of 2016 terrorist attack in Nice, France in less than 12 hours.
  • Work won Silver medal at Malofiej 2017, and gold at Society of News and Design.

Selected Publications, Posters, and Talks

Building a software package in tandem with machine learning methods research can result in both more rigorous code and more rigorous research

ENAR 2020

N/A

2020

  • Invited talk in Human Data Interaction section.
  • How and why building an R package can benefit methodological research

Stochastic Block Modeling in R, Statistically rigorous clustering with rigorous code

RStudio::conf 2020

N/A

2020

  • Invited talk about new sbmR package.
  • Focus on how software development and methodological research can improve both benefit when done in tandem.

PheWAS-ME: A web-app for interactive exploration of multimorbidity patterns in PheWAS

Bioinformatics

N/A

2020

  • Manuscript detailing application for the exploration of multimorbidity patterns in PheWAS analyses
  • See landing page for more information.

Charge Reductions Associated with Shortening Time to Recovery in Septic Shock

Chest

N/A

2019

  • Authored with Wesley H. Self, MD MPH; Dandan Liu, PhD; Stephan Russ, MD, MPH; Michael J. Ward, MD, PhD, MBA; Nathan I. Shapiro, MD, MPH; Todd W. Rice, MD, MSc; Matthew W. Semler, MD, MSc.

Multimorbidity Explorer | A shiny app for exploring EHR and biobank data

RStudio::conf 2019

N/A

2019

  • Contributed Poster. Authored with Yaomin Xu.

Taking a network view of EHR and Biobank data to find explainable multivariate patterns

Vanderbilt Biostatistics Seminar Series

N/A

2019

  • University wide seminar series.

Patient-specific risk factors independently influence survival in Myelodysplastic Syndromes in an unbiased review of EHR records

Under-Review (copy available upon request.)

N/A

2019

  • Bayesian network analysis used to find novel subgroups of patients with Myelodysplastic Syndromes (MDS).
  • Analysis done using method built for my dissertation.

Patient specific comorbidities impact overall survival in myelofibrosis

Under-Review (copy available upon request.)

N/A

2019

  • Bayesian network analysis used to find robust novel subgroups of patients with given genetic mutations.
  • Analysis done using method built for my dissertation.

R timelineViz: Visualizing the distribution of study events in longitudinal studies

Under-Review (copy available upon request.)

N/A

2018

  • Authored with Alex Sunderman of the Vanderbilt Department of Epidemiology.

Continuous Classification using Deep Neural Networks

Vanderbilt Biostatistics Qualification Exam

N/A

2017

  • Review of methods for classifying continuous data streams using neural networks
  • Successfully met qualifying examination standards

Asymmetric Linkage Disequilibrium: Tools for Dissecting Multiallelic LD

Journal of Human Immunology

N/A

2015

  • Authored with Richard Single, Vanja Paunic, Mark Albrecht, and Martin Maiers.

An Agent Based Model of Mysis Migration

International Association of Great Lakes Research Conference

N/A

2015

  • Authored with Brian O’Malley, Sture Hansson, and Jason Stockwell.

Declines of Mysis diluviana in the Great Lakes

Journal of Great Lakes Research

N/A

2015

  • Authored with Peter Euclide and Jason Stockwell.