Summary
Josh Mancuso is a data-focused Team Lead and former professional poker player who brings eight years of diverse experience blending analytical rigor, probability-driven decision making, and hands-on machine learning. Trained in finance and law, he transitioned through Lambda School's Data Science track to lead and mentor cohorts of 40+ students, running agile team projects and providing detailed code reviews and one-on-one guidance. His technical toolkit centers on Python (NumPy, Pandas, scikit-learn), TensorFlow/Keras, NLP, and geospatial analysis, with applied projects ranging from NFL weather impacts to Tanzanian water-well prediction and a Goodreads-based recommendation system. Comfortable translating messy real-world data into predictive models and deployable web apps, he pairs curiosity and lifelong learning with a knack for teaching others how to think through complex problems. An unconventional background in high-stakes self-employment gives him unique resilience and probabilistic intuition that informs his approach to data-driven product decisions.
8 years of coding experience
Bachelor of Science - BS, Finance, General, Magna Cum Laude, Bachelor of Science - BS, Finance, General, Magna Cum Laude at Florida State University
Juris Doctor of Law - JD, Law, Juris Doctor of Law - JD, Law at Louisiana State University, Paul M. Hebert Law Center
Data Science Track, Data Science Track at Lambda School