Executive Director, Quantitative Research & Algorithmic Trading
London, UK | April 2009 – January 2012
From April 2009 to January 2012, I was an Executive Director within Goldman Sachs’ Global Markets Division in London. My primary responsibilities involved quantitative research and development of algorithmic execution strategies focused on the European equity markets. This included designing, implementing, and refining execution algorithms such as Volume Weighted Average Price (VWAP) and Implementation Shortfall.
During my tenure at Goldman Sachs, I collaborated closely with distinguished professionals who significantly contributed to our quantitative and algorithmic trading strategies:
Michael Seigne – Managing Director and Co-Head of EMEA Electronic Trading. Michael oversaw the development of high-performance algorithmic execution strategies and led strategic expansions within electronic trading across Europe.
Theo Bell – Specialist in quantitative execution strategies, particularly skilled in modeling market impact and refining execution algorithms such as VWAP and Implementation Shortfall, to enhance institutional client trading performance.
Justin Brickwood – Head of EMEA Equities Electronic Trading Engineering. Justin led engineering teams responsible for building the robust, high-throughput trading infrastructure that supported our systematic algorithmic trading activities.
George Sofianos – Renowned expert in market microstructure and Head of Equity Execution Strategies. George contributed extensively to the quantitative foundations underpinning our execution analytics, risk management techniques, and algorithmic trading innovations.
Kilian Mie – Vice President in Electronic Trading. Kilian actively contributed to developing and fine-tuning trading algorithms, particularly in adaptive and dynamic execution methods aimed at minimizing transaction costs and market impact.
Brad Hunt – Managing Director responsible for strategically expanding Goldman Sachs’ electronic trading capabilities in Europe. Brad provided leadership in client-focused initiatives, market expansion, and strategic oversight of algorithmic trading product development.
1. Quantitative Research
Conducted extensive quantitative research on market microstructure, liquidity dynamics, and transaction cost analysis.
Developed statistical models to predict intraday trading volumes and optimize execution strategies accordingly.
Enhanced algorithms to reduce market impact, slippage, and execution cost.
2. Algorithmic Execution Strategies
Designed and implemented industry-standard trading algorithms including:
VWAP (Volume Weighted Average Price): Algorithms designed to match or improve upon the daily volume-weighted average price by distributing trades proportionally to historical and real-time volume patterns.
Implementation Shortfall (IS): Algorithms aimed at minimizing the difference between the decision price and actual execution price, emphasizing immediate execution balanced with market impact control.
Improved algorithm performance through rigorous backtesting, real-time analysis, and iterative refinements.
3. Programming and Implementation
Developed execution algorithms and real-time analytics using advanced programming frameworks, predominantly leveraging Python, and proprietary quantitative libraries.
Built monitoring systems to track algorithm performance, including fill rates, slippage metrics, and market impact analysis.
4. Collaboration and Leadership
Collaborated closely with global trading desks, quantitative strategists, and clients to tailor and optimize execution algorithms according to specific trading objectives.
Led cross-functional initiatives to streamline trade execution and improve transparency, reporting, and client communication.
Implemented sophisticated predictive models (e.g., time-series analysis, regression models) to enhance VWAP execution accuracy.
Advanced statistical frameworks to minimize implementation shortfall, optimizing the trade-off between immediacy and market impact.
Built robust monitoring and execution analytics platforms for systematic real-time performance evaluation.
Successfully improved algorithmic execution efficiency, significantly reducing client transaction costs and market impact.
Developed algorithms that became a core offering in Goldman Sachs’ execution strategy suite for institutional clients in Europe.
Contributed to internal thought leadership and client education, regularly presenting strategy developments and analytics improvements.
The developed execution algorithms and analytics frameworks played a key role in Goldman Sachs’ market-leading position within algorithmic trading in European equities, receiving positive client feedback for performance reliability and transparency.
During my tenure at Goldman Sachs, I significantly advanced the quantitative modeling and algorithmic execution capabilities in the European equity markets, achieving measurable improvements in execution quality, reducing costs, and enhancing client satisfaction.