Designed two 12-unit courses for BSc and MSc. students (including CMU’s top ranked Computer Sciences and Master of Science in Computational Finance programs) on Advanced Financial Quantitative Analysis and Algorithmic Trading:• Teaching data-driven decision making, scientific research practices, and principles of evidence based technical analysis (20% theoretical & 80% practical implementation of strategy development and algorithmic trading best practices)• Material includes Python-based research infrastructure development and quantitative research, risk management, execution related best practices.• Teaching BSc. and MSc. students including of the Computer Sciences Department widely recognized as among the top 3 CS programs in the world, also including Statistics & Data Science department of the Dietrich College, and Master of Science in Computational Finance (MSCF) students of the Tepper School of Business• Co-Founded Institute for Algorithmic Trading and Applied Computational Finance with 2 other faculty members• Faculty page & syllabus on https://benracz.com

Head of Quantitative Research & Managing Director @ Algorithmic Sciences Founded Algorithmic Sciences (http://algosciences.com); Quant Finance Scientific Research & Software Consulting Firm.Core Accomplishments:• Developed 21 member global team of systematically vetted and proven scientists, engineers, and consultants• Developed and tested 3 institutional grade validation procedures for positive expectancy algorithmic trading systems• Systems generated 350% return (out of sample) in 3.5 year period and maintained ensuring profitability• Created POC of validation procedure that generates 100s of trading systems executing 10,000+ trades/year. (5 losing months in 10 year period of testing)• Developed statistics & behavioral analysis based proprietary automated risk management system for US-based Prop Fund/CTA with 25k active live accounts to automatically mitigate losses based on historical performance• Developed IP to predict the spread, saving 80-90% spread costs when executing buy side strategies at FX brokers• Developed grid-based distributed backtesting platform to run 2mil backtests/hour/server on retail infrastructure (no GPUs)• Wrote execution stack to execute 100k+ trading strategies simultaneously to multiple venues; Combined 7 μs loop time on critical path for new tick discovery and strategy execution on 28 instruments (no FPGA-s); Includes A & B books, netting algorithm, data aggregation and a matching engine to reduce costs)• Developed OEMS to execute order flow while using novel procedures to continuously evaluate and optimize a HFT meta-strategies layer that optimizes costs

• 2008-2012; & 2021 Data Science/Software driven wholesale ecommerce business which used predictive analytics to identify market mispricings of tens of thousands of used products in secondary markets at 99.97% accuracy in 27 different countries. Set up and managed operations to buy and resell for profit.• 2013-2020; CTO/Strategic Consulting focused on data driven & quantitative methodologies as applied to media buying, ad campaign performance, reputation/risk management, and lead generation.• 2006-2016; Managing Director for private intelligence and information security consulting firm performing security auditing, software development and infrastructure operations related to ISO, SOC Compliance, PCI-DSS Requirements, Firewalls, Linux Kernel Audits, and Vulnerability Assessments, including performing as Director of Security at NASDAQ-traded firm.