Wall Street Soaks Up Software Talent

By Robert Gelber

September 3, 2012

Fortune writer Christopher Steiner has just released a new book called Automate This: How Algorithms Came to Rule Our World. His work discusses the prevalence of algorithms in modern society and how industries compete for the developers that create them.  This is especially true on Wall Street, where deep-pocketed financial institutions place a high value on such talent.  The pay scales and benefits packages for this class of developers on Wall Street far outweigh those offered by startups with venture capital funding or run-of-the-mill institutions in need of algorithmic specialists. In an interview with Fast Company, Steiner explained how the financial industry is tempting valuable coders away from other organizations that require their talents.

Steiner believes that developers who create algorithms are the “preeminent entrepreneurs of this generation.” Their ability to build something from nothing makes them a highly sought-after commodity. “Your average developer’s going to make a nice salary,” he said, “but if that person innovates with code that ‘solves a problem’ the opportunities are huge.”

These same talents are attractive to venture capital firms, because initial costs are extremely low. The product is simply an idea that transforms information into a high-value commodity.  Unfortunately, enticing algorithmic chefs to join a Silicon Valley startup has become difficult given the value financial firms have placed on these individuals. Steiner says that people don’t appreciate the number of developers Wall Street has taken off the market. During similar situations in the past, Silicon Valley companies couldn’t compete with the level of compensation offered by the financial industry — not to mention the status of working for a prestigious New York firm.              

On the other hand, startups offer developers the chance to deliver a positive impact on their society. If a coder chooses to work with a company that improves the efficiency of healthcare or reduces energy consumption by double-digit percentages, they contribute to the nation’s well being.  Conversely, Steiner thinks that building algorithms for a Goldman Sachs or JP Morgan has far less potential for providing social good.

Worse, something this line of work leads to seriously awful outcomes. Steiner attributes some of this to Wall Street’s culture of speed over accuracy. In classic scenarios, developers constantly test their creations, looking for defects and edge cases. He mentioned that Google tests an algorithm a hundred million times before it gets released into the market. Financial institutions are quite the opposite. Firms are so consumed with turnaround time that developers don’t have the capacity to properly vet their code. New algorithms go into production every couple of weeks, and on occasion, go rogue.

Take for example, the Flash Crash of 2010, which resulted in a 1,000-point swing on the Dow Jones industrial, and more recently, this year’s Knight’s Capital debacle, which caused the firm to lose $440 million in a single day. Both were the result of algorithms run amuck.

 

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