Burton Dewilde - Data Science Engineer

Burton Dewilde

Data Science Engineer

Burlington, Vermont, United States

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Summary

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Rockstar

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Top School

Burton Dewilde is a Data Science Engineer with 13 years of experience building end-to-end data products, production-ready code, and ML pipelines, currently modernizing database interfaces and detecting EV home charging at WeaveGrid. He has a strong journalism- and research-informed background from Chartbeat and Harmony Institute, where he turned web analytics and mixed-methods research into actionable tooling and editorial insights. Comfortable across backend systems and QA, Burton is an active open-source contributor—helping parse Google Trends in pytrends, extend real-time processing in streamz, and harden tests in the dragnet web-extraction project. He pairs a PhD-level physics foundation and rigorous statistical thinking with hands-on engineering, from C++ data acquisition frameworks to Python production code. Based in Burlington, VT, he brings a knack for scoping consulting-style projects into deployable systems and an unusual blend of particle-physics analysis rigor and practical product delivery.

13 years of coding experience

16 years of employment as a software developer

Bachelor of Arts (B.A.), Physics and Spanish, 4.0, Bachelor of Arts (B.A.), Physics and Spanish, 4.0 at Kalamazoo College

Doctor of Philosophy - PhD, Physics, 3.86, Doctor of Philosophy - PhD, Physics, 3.86 at Stony Brook University

Spanish, French

Github Skills (21)

unit-testing10

apim10

pytest10

python10

async10

testing10

data-parsing10

csv-parser10

api10

csv10

streaming-data10

realtime9

conversions9

data-conversion9

hash9

Programming languages (10)

TypeScriptJavaShellCSSRustVueHTMLJupyter Notebook

Github contributions (5)

dragnet-org/dragnet

Apr 2019 - Jul 2019

Just the facts -- web page content extraction

Role in this project:

QA Engineer / Test Automation Engineer

Contributions:1 release, 22 commits, 10 PRs in 3 months

Contributions summary:Burton primarily focused on porting existing tests to the pytest framework. Their work involved modifying and updating test files across multiple modules, including `test_blocks.py`, `test_data_processing.py`, `test_extractor.py`, `test_kohlschuetter.py`, `test_lcs.py`, `test_models.py`, `test_readability.py`, `test_util.py`, and `test_weninger.py`. These changes updated testing implementations and refactored dependencies to ensure test functionality.

extractionpythoncontent-extractionfactsweb-page

GeneralMills/pytrends

Aug 2015 - Aug 2015

Pseudo API for Google Trends

Role in this project:

Back-end Developer

Contributions:13 commits, 5 PRs, 26 pushes in 12 days

Contributions summary:Burton's primary contribution involves developing features for parsing and processing data within the `pytrends` library. They implemented functions to parse CSV data from Google Trends into a JSON format, including handling date conversions and data type inference. Further contributions included bug fixes for date formats and percentage handling, along with refactoring code for improved Python 2/3 compatibility and code organization. This work demonstrates a focus on data processing and API interaction with Google Trends.

pseudoapigoogle-trendstrends

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