Jenny Long is an Analytics Engineer based in New York with five years of experience blending machine learning research, data productization, and growth analytics. She has driven analytics and growth strategy at Datadog and now builds analytics infrastructure at Profound after advising PE firms on over 25 software and TMT deals at EY-Parthenon. Her background includes pre-doctoral CS work at the University of Chicago and research on interpretable attention models at McGill, where she applied those techniques to both text and neuroscience data. Comfortable moving models from prototype to production, she has practical experience in NLP, transfer learning, and building extraction pipelines for real-world risk detection. Known for bridging rigorous quantitative analysis with clear communication, she also brings hands-on experience organizing AI communities and teaching advanced ML topics.
5 years of coding experience
4 years of employment as a software developer
DEC Arts and Science , DEC Arts and Science at Marianopolis College
Pre-Doctoral MS Computer Science, Pre-Doctoral MS Computer Science at University of Chicago
Bachelor's degree Physics and Computer Science Rossy Leader Scholarship, Bachelor's degree Physics and Computer Science Rossy Leader Scholarship at McGill University
Contributions:10 commits, 9 PRs, 3 pushes in 10 months
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