William Koehrsen
Senior Software Engineer at Grid Status
Washington, District of Columbia, United States
Summary
🤩
Rockstar🎓
Top SchoolWilliam Koehrsen is a Senior Software Engineer with nine years of experience building production ML systems and energy-focused products, currently at Grid Status in Washington, D.C. He has led end-to-end machine learning pipelines and DevOps for real-time energy-efficiency recommendations, shipping customer-facing features at scale while managing cloud deployments and infrastructure. His background blends mechanical engineering and advanced CS training (Georgia Tech MS) with hands-on work in feature engineering, RNNs, and tooling—contributing to the popular open-source Featuretools project and authoring instructional visualization and ML walkthroughs. Known for turning research-grade analytics into reliable products, he pairs deep data-science expertise with full-stack engineering to close the loop from data ingestion through production delivery.
9 years of coding experience
7 years of employment as a software developer
Deep Learning Specialization, Deep Learning Specialization at CourseraBachelor’s Degree Mechanical Engineering, Bachelor’s Degree Mechanical Engineering at Case Western Reserve UniversityData Analyst Nanodegree, Data Analyst Nanodegree at UdacityHigh School Diploma High School/Secondary Diplomas and Certificates, High School Diploma High School/Secondary Diplomas and Certificates at Metamora Township High SchoolMaster of Science - MS Computer Science, Master of Science - MS Computer Science at Georgia Institute of Technology
English, python, r
Stackoverflow
3,757reputation
216kreached
41answers
12questions
csv
top-5%
visual-studio-code
top-5%
python
top-5%
Github Skills (47)
data-visualizations10
bokeh10
python10
scikit10
pandas10
machine-learning10
rnn-model10
data-visualisation10
exploratory-data-analysis10
feature-engineering10
n10
data-preprocessing10
keras10
lstm10
tensorflow10
Programming languages (8)
Github contributions (5)
WillKoehrsen/wikipedia-data-science
Sep 2018 - Oct 2018
Working with and analyzing Wikipedia Data
Role in this project:
Data Scientist
Data ScientistContributions:93 commits, 4 PRs, 81 pushes in 1 month
Contributions summary:William's commits focus on working with and analyzing Wikipedia data. Their work involves downloading and parsing Wikipedia articles, demonstrating an understanding of data acquisition and preprocessing. Furthermore, the user employs machine learning techniques by preparing to build an entity embedding model.
analyzingcorpuswikipedia-datawikipediadata-visualization
alteryx/predict-customer-churn
Sep 2018 - Nov 2018
A general-purpose framework for solving problems with machine learning applied to predicting customer churn
Role in this project:ML Engineer
ML EngineerContributions:134 commits, 20 pushes, 1 branch in 2 months
Contributions summary:William focused on feature engineering and building machine learning models for customer churn prediction within the Alteryx framework. Their contributions involved adding and modifying Python notebooks, likely implementing and experimenting with different feature engineering techniques and exploring model training/evaluation. The changes involved reading, merging and transforming data for use in machine learning, a common pattern in data science projects.
appliedpythonsolvingproblemsmachine-learning
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