JackĀ Goldsmith
Student
New York, New York, United States
Summary
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Rockstarš
Top SchoolJack Goldsmith is a computer science student based in New York with nine years of hands-on software experience and active contributions to high-profile open-source projects. He has backend and data-focused expertise, notably refactoring Scala code and adding GenomicsDB integration and plotting/aggregation features to the cloud-native Hail genomics project. He has also contributed to pandas by improving documentation, tests, and type-handling for data selection and construction. Comfortable across languages and data tooling, Jack blends practical engineering with attention to correctness and reproducibility. His academic path spans Boston University and Queens College, reflecting a sustained commitment to CS while contributing meaningfully to production-grade libraries. An often-overlooked strength is his attention to legacy-cleanup and test coverage, which helps codebases stay maintainable as they scale.
9 years of coding experience
High School Diploma, High School Diploma at John L. Miller Great Neck North High SchoolBachelor of Arts - BA, Computer Science, Bachelor of Arts - BA, Computer Science at Queens CollegeComputer Science, Computer Science at Boston University
English, Korean, Latin
Github Skills (13)
scala10
hail10
pandas10
bioinformatics10
genomics10
python10
data-analysis10
vcf-files9
data-science9
documentation9
genetics9
data-engineering8
testing8
Programming languages (6)
Github contributions (5)
hail-is/hail
Jun 2017 - Aug 2018
Cloud-native genomic dataframes and batch computing
Role in this project:
Back-end Developer
Back-end DeveloperContributions:10 commits, 16 PRs, 5 pushes in 1 year 1 month
Contributions summary:Jack primarily contributed to the Hail project by refactoring and removing deprecated code elements, such as the `Accumulable` class. They also introduced new functionality, specifically related to GenomicsDB integration, including the addition of JSON files and the implementation of test suites. The user demonstrated expertise in modifying Scala code, as well as creating new functions for plotting and data aggregation.
scalabledata-analysispythongeneticshail
pandas-dev/pandas
May 2022 - Jun 2022
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Role in this project:Data Scientist
Data ScientistContributions:9 commits, 9 PRs, 29 comments in 26 days
Contributions summary:Jack contributed to the pandas library by fixing documentation errors and improving clarity in several areas. They addressed typos and enhanced the documentation for functions like `tz_convert`, `corr`, `cov`, and others. The user also added tests to ensure the correct behavior and type handling of data, specifically for `loc` functions and multi-column dtype assignments. Furthermore, they improved the period constructor documentation.
pythondatalabeled-datamanipulationdataframes
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