Dal Williams
Scientist at Snapdragon Chemistry, Inc.
Somerville, Massachusetts, United States
Summary
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Rockstar🎓
Top SchoolDal Williams is a scientist and machine learning engineer with seven years of experience bridging physical organic chemistry and data-driven research. Currently at Snapdragon Chemistry, he applies ML, automation, and reproducible data practices to accelerate chemistry and adjacent domains like energy and biotech. His background includes a PhD in chemistry, hands-on synthesis and analytical characterization, automated reaction monitoring at Fluence Analytics, and building an image-recognition recycling prototype during a data science fellowship. Dal contributes to open-source data-cleaning tooling (pyjanitor), improving testing, documentation, and practical utilities that reflect his focus on robust pipelines and deployment. He is particularly interested in semi-supervised learning, computer vision, and production-ready testing—skills he leverages to empower scientists and make experimental workflows more reliable and scalable.
7 years of coding experience
9 years of employment as a software developer
Bachelor's degree, Major: Chemistry, Minor: Business Administration, Bachelor's degree, Major: Chemistry, Minor: Business Administration at University of Tennessee-KnoxvilleDoctor of Philosophy - PhD, Chemistry, Doctor of Philosophy - PhD, Chemistry at University of Mississippi
English, French
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (11)
dataframes10
pandas10
pytest10
data-cleaning10
python10
dataframe10
data-engineering10
user-data9
data-model9
data-set9
documentation8
Programming languages (3)
Github contributions (5)
pyjanitor-devs/pyjanitor
May 2019 - Nov 2019
Clean APIs for data cleaning. Python implementation of R package Janitor
Role in this project:
Data Engineer
Data EngineerContributions:5 commits, 7 PRs, 13 comments in 5 months
Contributions summary:Dal primarily contributed to improving the pyjanitor library, focusing on data cleaning functionalities. Their work involved refactoring and adding test cases, as well as expanding the documentation. The user also implemented new methods, fixed style errors, and added enhancements to existing features, like adding currency conversions and improved documentation for coalesce functionality. They also addressed development dependencies.
data-cleaningpythonrr-packagepandas
dendrondal/Recyclops
Aug 2019 - Oct 2020
Contributions:175 commits, 84 pushes, 4 branches in 1 year 2 months
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