Summary
Steve Draper is a Senior Data Scientist in Austin with nine years focused on machine learning and a decades-long software engineering pedigree stretching back to systems work at IBM and Novell. He combines deep expertise in NLP and structured-data modeling—recently building reading-error models from children's audio at Amira Learning—with strong foundations in deep learning, optimization, and functional programming. Steve has translated research on fairness, explainability, and latent-space analysis into production at CognitiveScale, pairing PyTorch models with genetic-algorithm and autoencoder-driven investigations. Comfortable across the stack, he has hands-on experience designing inference engines, streaming pipelines (including Haskell-based processing), and scalable microservices in Scala. His background as a co-founder and architect of an incremental replication system shows a rare mix of low-level distributed-systems craftsmanship and modern ML product delivery.
9 years of coding experience
34 years of employment as a software developer
Coursera
Bachelor's Degree, Mathematics, 2i, Bachelor's Degree, Mathematics, 2i at University of Cambridge