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Assistant Professor in the Department of Computer Science at the Rochester Institute of Technology
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Rochester Institute of Technology
Data Scientist
June 24, 2026 – Present
blaze
October 15, 2024 – Present
The ultra high-performance C++ JSON Schema validator, providing validation even down to the nano-second range (depends on schemas and hardware) along with perfect compliance scores. Supports Draft 4, Draft 6, Draft 7, 2019-09 and 2020-12. For both servers and embedded devices
View Projectcore
December 8, 2022 – Present
A comprehensive set of composable foundational C++ libraries and CMake utilities to power Sourcemeta projects. Note we don't provide any stable ABI/API guarantees to external users outside Sourcemeta
View Projectcalcite-notebooks
December 19, 2018 – August 10, 2020
:notebook: A series of Jupyter notebooks to demonstrate the functionality of Apache Calcite
View Projectzotero-remarkable
March 18, 2018 – June 1, 2020
Sync papers from Zotero to a reMarkable tablet
View Projectcalcite-test-dataset
January 25, 2015 – March 24, 2023
Data sets and Vagrant script to provision a virtual machine for Apache Calcite development
View ProjectSentencer
October 11, 2014 – December 3, 2022
:pencil2: madlibs-style sentence templating in Javascript
View Projectmvptree
January 21, 2012 – February 20, 2018
A fork of D Grant Starkweather's multiple vantage point tree library
View Projectw3c_validators
December 31, 2008 – July 22, 2023
A Ruby wrapper for the World Wide Web Consortium’s online validation services.
View ProjectCultural Fit Analysis
The candidate's extensive list of personal projects across various technologies (PHP, Jupyter Notebook, C++, Scala, JavaScript, Java, Ruby, HTML, Objective C, Python) indicates a strong curiosity and a drive for self-improvement, which can be a positive cultural fit. However, the projects are predominantly personal and lack explicit team collaboration or large-scale enterprise context, making it difficult to fully assess cultural fit for a collaborative team environment. The target role is 'Data Scientist', and while some projects touch upon data-related concepts (e.g., 'calcite-notebooks', 'jsonoid-discovery', 'NoSE'), the overall project portfolio is very broad and not sharply focused on typical data science methodologies (e.g., machine learning, statistical modeling, advanced analytics). The single listed professional experience as 'Data Scientist' is current but lacks details, making it hard to gauge alignment with the target role's specific requirements.
Soft Skills & Operational Fit
The candidate's personal projects demonstrate initiative and a proactive approach to problem-solving. The diversity of technologies used suggests adaptability. However, without psychometric test results or interview data, it is difficult to assess other soft skills like teamwork, stress handling, or communication clarity in a professional context.