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Assessing your cultural and operational fit
New York University
Data Scientist
June 24, 2026 – Present
nyphil-programming-analysis
October 13, 2024 – December 13, 2024
Analysis of the New York Philharmonic Performance History
View Projectinvenio-gis-previewer
August 30, 2021 – September 3, 2024
invenio-gis-previewer — GitHub repository
View Projectspn-techinfra-emulation
June 21, 2021 – December 6, 2021
Community resource for emulation use cases
View Projecthumanizing-data-2017
April 4, 2017 – August 7, 2017
humanizing-data-2017 — GitHub repository
View ProjectReproducibility-ReproZip
March 7, 2017 – Present
An overview of reproducibility at large and a tool to enable reproducibility, ReproZip
View ProjectGitHub-OSF-OpenResearch
February 14, 2017 – February 21, 2018
Slides for a class on connecting GitHub to the Open Science Framework for open scholarship.
View ProjectDataScience-Citation-Workshop
August 4, 2016 – Present
A workshop on citing and being cited for atypical research materials.
View Project2016-NDSR-CompetencyProfile-Paper
May 26, 2016 – March 29, 2017
A paper by Karl-Rainer Blumenthal, Peggy Griesinger, Julia Kim, and Vicky Steeves on the National Digital Stewardship Residency program.
View Projectpersonal-website
May 11, 2016 – March 18, 2021
The code behind my sort-of professional site.
View ProjectCultural Fit Analysis
The candidate's projects primarily focus on academic, archival, and web development contexts, with a strong emphasis on open science and digital humanities. While there is a current Data Scientist role, the project portfolio leans more towards web development and academic research support rather than core data science applications like machine learning, statistical modeling, or large-scale data processing. This suggests a potential mismatch with typical industry Data Scientist roles that require a strong focus on predictive analytics or product development.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. Psychometric test scores are 0, providing no insight.