# Jay Trevino > Lead SWE @ Worth Venture Partners Location: New York, New York, United States Profile: https://flows.cv/jaytrevino Focused on the 0-to-1 development of high-stakes production environments. Currently responsible for the end-to-end technical lifecycle of a well-funded trading system, spanning data ingestion, transformation, and automated execution. Expertise involves bridging backend infrastructure with machine learning orchestration, specifically integrating LLMs and reinforcement learning into modular, low-latency pipelines. Proven track record of maintaining high-integrity production systems with total autonomy, serving as the primary lead for mission-critical troubleshooting and system scaling. Specialization includes optimizing complex computational workflows through strategic caching and real-time statistical diagnostics to compress multi-week research cycles into single-day delivery. Focused on building scalable, production-grade architecture for lean, high-output teams where technical ownership and operational reliability are paramount. ## Work Experience ### Lead Software Engineer @ Worth Venture Partners Jan 2025 – Present | New York, New York, United States Architected and owned the end-to-end data infrastructure for trading system, integrating Bloomberg and open-source APIs into high-availability ingestion pipelines. Engineered a modular backend to automate complex workflows and research cycles, ensuring seamless scalability and operational stability. Established a production-grade deployment environment via Docker and AWS to ensure high-integrity execution and system reliability. Focused on building high-ownership, 0-to-1 systems where technical autonomy is the baseline. ### Software Engineer @ Rosetta Analytics - AI Asset Management Jan 2023 – Jan 2024 | New York, New York, United States Redesigned the core trading platform monitoring up to $90M in daily trades, adding early failure detection to prevent downtime. Built a machine learning strategy to benchmark internal RL research and contributed regularly to strategy reviews and paper discussions. Also developed analytics used directly in investor pitch decks to support fundraising. ### Data Science Researcher @ Rights CoLab Jan 2021 – Jan 2023 | New York, New York, United States Data for Good Scholar. Worked at the intersection of data science and human rights policy. Partnered with Rights CoLab and the ISSB to extract financially material ESG language using NLP and data science, in an effort to standardize human rights policies global. Built custom web scrapers and scripting pipelines to collect and process financial disclosures from international sources. ### Cloud FinOps Data Analyst Intern @ Workday Jan 2022 – Jan 2022 | Pleasanton, California, United States Built interactive dashboards in Looker to monitor cloud spend and usage, surfacing key trends and inefficiencies. Helped identify ~$10K/month in potential savings and improved visibility across 50+ KPIs. ### Data Engineering Intern @ Columbia Build Lab Jan 2021 – Jan 2022 | New York, New York, United States In partnership with Columbia Build Lab and Columbia Business School. Built a full data pipeline from scratch using NLP to extract insights from interview audio. Designed backend systems to process, store, and serve results, enabling real-time visualizations in Tableau. ### Astronomy REU Data Science Intern @ The University of Texas at Austin Jan 2021 – Jan 2021 | Austin, Texas, United States Applied data science techniques to model and analyze CLASSY galaxies as part of a Hubble-based spectral survey. Worked with far-UV data to study star-forming galaxies, contributing to the first high-resolution spectral database of its kind. CLASSY is a treasury survey that builds on the Hubble Space Telescope (HST) archive to construct the first high-quality, high-resolution far-ultra violet (far-UV) spectral database of nearby star-forming galaxies. ### Statistical Cosmology Researcher @ Columbia University in the City of New York Jan 2020 – Jan 2021 | New York, New York, United States Used high-performance computing and Linux-based systems to run statistical analyses on large-scale cosmology datasets. Focused on cleaning CMB foregrounds by identifying and minimizing contamination from galactic dust. ## Education ### Bachelor's degree in Computer Science Columbia University Jan 2019 – Jan 2023 ## Contact & Social - LinkedIn: https://linkedin.com/in/jayalexandertrevino - GitHub: https://github.com/jat2211 --- Source: https://flows.cv/jaytrevino JSON Resume: https://flows.cv/jaytrevino/resume.json Last updated: 2026-04-01