Karl Lorey
Founder at startupradar.co
Berlin, Germany
Summary
🤩
Rockstar🎓
Top SchoolKarl Lorey is a Berlin-based founder and engineer with 10 years of experience building data-driven startups and tooling for early-stage venture sourcing. He co-founded First Momentum Ventures (a €5M early-stage fund) and embedded scrapers and machine learning into the investment workflow to surface opportunities earlier, later productizing that work via startupradar.co. Technically hands-on, he prototypes ML-powered scraping—his mlscraper work includes a decision-tree element detector—and routinely ships pragmatic Python/SQL/JS stacks to take projects from MVP to Seed. His background includes published research at KIT on encrypted database storage, reflecting a blend of applied research and product engineering. Today he runs apistemic and startupradar.co, combining VC domain knowledge, crawling/ML expertise, and founder-level product instincts to turn noisy web data into actionable signals.
11 years of coding experience
6 years of employment as a software developer
A+, with distinction, A+, with distinction at Karlsruhe Institute of Technology (KIT)
English, French, German
Stackoverflow
1,576reputation
154kreached
26answers
3questions
php
top-5%
laravel
top-5%
Github Skills (21)
python10
scikit10
scikit-learn10
decision-tree10
laravel9
machine-learning9
php9
web-scraping8
beautifulsoup8
scraper7
pandas7
crawler7
nested6
html6
phantomjs6
Programming languages (11)
Github contributions (5)
lorey/mlscraper
Jun 2020 - Jan 2023
🤖 Scrape data from HTML websites automatically by just providing examples
Role in this project:
ML Engineer
ML EngineerContributions:2 releases, 122 commits, 1 PR in 2 years 7 months
Contributions summary:Karl primarily focused on implementing machine-learning-based functionality within the mlscraper project. They added a prototype utilizing a decision tree classifier for element detection on websites, demonstrating an understanding of machine learning principles. The user's work included defining preprocessing steps and training a pipeline for classification tasks. Furthermore, they integrated and tested the model on a website, showcasing their ability to apply machine learning to a real-world scraping problem.
extraction-enginepythonscrapyscrapemachine-learning
germanitjobs/perfect-german-cv
Sep 2016 - Apr 2017
Contributions:12 commits, 9 pushes, 1 branch in 7 months
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