Dakota Denison
Quantitative Developer
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolDakota Denison is a quantitative developer in New York with eight years of experience building data and machine learning systems for trading and research across crypto, finance, and public policy. Proficient in Python, R, SQL, and frameworks from PyTorch to tidymodels, Dakota designs end-to-end pipelines, backtests statistical-arbitrage strategies, and implements production-grade data engineering on AWS, Kafka, Airflow, and Spark. Their background spans DeFi protocol analysis, tokenomics and AMM modeling to hierarchical causal inference and custom deep-learning loss functions for social-program evaluation, reflecting a rare blend of financial engineering and rigorous econometric training. Comfortable in both research and production contexts, Dakota has repeatedly turned noisy, high-frequency data into robust signals and risk models for desks and policy researchers alike. Notably, they pair a formal economics education with a creative side rooted in jazz studies, suggesting a disciplined yet improvisational approach to problem solving.
8 years of coding experience
7 years of employment as a software developer
Bachelor’s Degree Economics minor in Mathematics, Bachelor’s Degree Economics minor in Mathematics at University of MichiganJazz Studies, Jazz Studies at Wayne State University
English, Spanish
Github Skills (4)
monte-carlo5
cryptocurrency3
python3
jupyter-notebook3
Programming languages (1)
Github contributions (5)
denisond/nycjazztonight
Jul 2019 - Dec 2021
Contributions:16 pushes, 2 branches in 2 years 5 months
denisond/nyc-property-price-deep-learning-demo
Sep 2021 - Oct 2021
Contributions:24 commits in 1 month
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