Scott Sykowski
Education
The University of Chicago Booth School of Business
Executive Education, Behavioral Economics 2024-01-01 - 2024-05-01
University at Albany
MBA, Finance 1988-01-01 - 1990-01-01
SUNY New Paltz
BA, Economics 1985-01-01 - 1988-01-01Work Experience
Time to Give Network
Current
Time to Give Network
Athena Systems
2006-04-01 - 2024-09-01
Athena Systems
The Macgregor Group
1998-01-01 - 2006-03-01
The Macgregor Group
ITG
2006-01-01 - 2006-01-01
ITG
Merrin Financial
1998-01-01 - 1999-01-01
Merrin Financial
EJV Partners
1995-01-01 - 1998-01-01
EJV Partners
Bridge Information Systems
1995-01-01 - 1998-01-01
Bridge Information Systems
Golden Harris
1993-01-01 - 1995-01-01
Golden Harris
Lebenthal
1990-01-01 - 1993-01-01
Lebenthal
United States Army Reserve
1982-01-01 - 1986-01-01
United States Army Reserve
Skills
Summary
Fintech thought-leader on analytics, decision support, and risk systems, with over 35 years in the industry. Architect of multiple world-class quantitative analytics and business process automation tools for buy-side and sell-side financial services firms. Extensive knowledge of the intricacies of most asset classes including vanilla fixed income, securitized (including mortgages, ABS and syndicated loans and CLOs), credit and interest derivatives. And of course, all the easy exchange traded instruments. Recent projects include: - Scenario analysis/stress testing with shifting of the underlying benchmark/index, volatility, or currency. - Realtime liquidity risk measurements and alerts. - Value-at-Risk (VaR )calculations with support for several different models including user tunable Monte Carlo and historical. - Various flavors of options pricing models. - Fund and firm level capitalization/margin stress testing. (Reg-T, TIMS, STANS, Portfolio Margin receiving FINRA approval at 3 different BDs). - Open/Tunable a priori Factor Model. - Brinson Performance Attribution extend for fixed income effects. Currently engaged in research for application of artificial intelligence to such problems as: benchmark approximation and portfolio construction, momentum analysis, block trade execution, margin/loss prediction, sentiment analysis, and data reconciliation. Ardent believer that a small team of exceptional talent is worth 10x that of larger mediocre teams. Top decile knowledge of Python, PyTorch, Pandas, Java/Node, SQL, and .net.
