Team and Advisory Board
Trading Technology. Credit Markets. Quantitative Finance. Machine Learning.
17 years of successful career in credit trading and risk. Prior to co-founding 7 Chord, Kristina worked at Blackrock, where she advised senior executives on risk trends resulting from market structure changes, in particular central clearing. She represented the firm on the CME CE Risk Committee and various industry forums. At JP Morgan she gained an invaluable business management experience as a key member of an award-winning derivatives clearing team that built a brand new fintech business. She spent the first 9 years of her career at Bear, Stearns and Scotia Capital in credit derivatives trading and structuring. She was initially hired by Bear, Stearns as part of the formal credit training program run by the counterparty credit department. Her very first project was related to the immediate aftermath of the near collapse of the Long-Term Capital Management. BA in Economics from NYU and MS in Finance from LSE.
HEAD OF MACHINE LEARNING RESEARCH
Roy has worked at the intersection of business strategy and technology for almost 40 years. Former CTO at Capital One and at Reuters and a management consultant at McKinsey and Co, in recent years he designed and guided the development of the Center for Data Science at NYU. The Center became a focal point for the university-wide initiatives in data science and statistics. The Center’s flagship MS in Data Science (MSDS) program received ~1300 applications for admission in fall 2016 and matriculated 232 students in total. Every single graduate became employed in data science or enrolled in a PhD program. He is also a founder of Advanced Valuation Analytics Corporation, where he develops real estate valuation and mortgage default prediction models. Roy has a PhD in machine learning from NYU with application to real estate, a MBA from Harvard and a BA in Math from Vanderbilt University.
CTO / COO
Pat serves as an interim CTO and advisor to several early stage ventures. Through modern platform design and architecture, Pat has helped established brokers and sell side institutions differentiate their trading and data businesses, outpacing revenue growth among their peers. Prior to his consulting practice, Pat led the overall technology strategy for fixed income and credit derivative trading at ICE. He served as a Head of Information Systems at Creditex Group until the firm was acquired by ICE in 2008. He has a MS in Technology Management from Columbia University and a BA from Saint Bonaventure University.
TRADING TECHNOLOGY ADVISOR
Jim is an accomplished CTO with extensive expertise in credit trading technology. Jim currently serves as a CTO of InterNex Capital, a digital lender providing innovative, efficient, and flexible working capital financing to small and medium sized businesses. Prior to that, as a co-founder and CTO at trueEX, he conceived vision and strategy of the company and implemented multiple platforms to support trading of derivatives. Jim was the first employee and CTO of Creditex, one of the first electronic market places for Credit Default Swap trading. He has a MIS in Computer Science from Virginia Polytechnic Institute and State University.
MACHINE LEARNING, CONSULTANT AND ADVISOR
Dennis is a professor of computer science at the Courant Institute of NYU and an Associate Director of NYU Wireless. He is known in the quantitative trading field for his research in pattern discovery in time series and for his work in array databases for time series analysis. Professor Shasha is a prolific author, researcher, and public speaker. His extensive resume can be found here: www.cs.nyu.edu/shasha. For fun he has created many mathematical puzzles, including for Scientific American. Dennis has a PhD from Harvard University in applied mathematics, M.Sc. from Syracuse University (overlapped work at IBM Data Systems Division) and B.Sc. from Yale University.
Join Our Team
We are looking for talented traders, software engineers and researchers who share our interest in cognitive computing and our bias towards automation. If you’re ready for a fresh start, drop us a note with your Linkedin and Github profiles:
We work with a small number of STEM graduate programs to identify future data scientists and machine learning engineers with the aptitude for quantitative trading. If you are a program administrator and would like us to come to your campus, please reach out to us at:
We offer Fall, Spring and Summer internships and are currently recruiting for Summer 2018.