|client:||Goldman Sachs Services Ltd|
|role:||Algorithmic & Quant Trading Strategist|
|time period:||Jun 2010 – Feb 2012|
data science • analytic cube • column-store databases • SAP IQ • Sybase IQ • Python • C • Linux
As a member of a small team of traders and strategists, I was the sole person responsible for the design, implementation, and continual improvement of our data-driven management decision support systems, and also conducted a great many one-off studies and analyses in response to immediate business needs.
Our business was a self-contained high-frequency trading strategy, conducting Goldman Sachs’ on-exchange market making activities for the European equities markets.
Within that business, my infrastructure played a central role. The tabular and graphical representations underlying our management decision support system were of my own devising and quickly began to form a basic conceptual vocabulary used by senior management to talk to each other about business problems and to search for solutions.
The centrepiece of the infrastructure was a table consisting of tens of millions of records and well over a hundred columns, with information sourced through automated regular data import from a disparate set of data sources. The analytics infrastructure itself was also subject to frequent updates and changes to accommodate for the changing needs of the business in the fast-paced environment of high-frequency trading.