Charles Drotar
Senior Software Engineering Manager at Microsoft
Issaquah, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolCharles Drotar is a Senior Software Engineering Manager with a decade of experience building cloud-native IoT and AI infrastructure at Microsoft, after formative data engineering roles at Capital One and AT&T. He blends hands-on expertise in Java, Scala, and Python with productionizing ML and time-series tooling—contributing enhancements and MLOps fixes to pmdarima’s decomposition and diagnostics. His background spans big data ETL, Spark tuning, automated cloud provisioning, and computer-vision algorithm work, and he holds a patent pending for vehicle sensor IoT processing. Known for turning long-running data jobs into efficient pipelines and leading teams in Copilot Studio and frontline infrastructure, he combines technical depth with pragmatic automation to drive measurable business impact.
10 years of coding experience
11 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at University of WashingtonBachelor of Science (B.S.) Electrical Engineering, Bachelor of Science (B.S.) Electrical Engineering at University of North Texas
English
Stackoverflow
121reputation
4kreached
5answers
0questions
Github Skills (14)
forecasting10
machine-learning10
time-series10
forecast10
python10
data-analysis10
testing9
cicd8
html6
markdown6
raspberry-pi6
csv6
linux6
numpy6
Programming languages (2)
Github contributions (5)
alkaline-ml/pmdarima
Jul 2017 - Jan 2021
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
Role in this project:
Back-end Developer & MLOps Engineer
Back-end Developer & MLOps EngineerContributions:2 reviews, 78 commits, 29 PRs in 3 years 7 months
Contributions summary:Charles primarily focused on enhancements and maintenance related to the project's core functionality and deployment. They changed the project's setup to avoid naming collisions. The user added functionality for plot diagnostics and testing, as well as implementing fixes to the build process. They also added support for time series decomposition which points towards the users focus on expanding the statistical capabilities of the library.
forecastingfillpythontime-series-analysisvoid
charlesdrotar/accessiplot
Feb 2023 - Mar 2023
A python library to enhance the accessibility of matplotlib plots
Contributions:48 PRs, 119 pushes, 49 branches in 1 month
accessibilitypython
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