Because of their ubiquity in today’s financial markets, a baseline familiarity with algorithmic trading is increasingly essential for careers as a trader, analyst, portfolio manager, or other finance jobs. These highly-paid professionals may work at institutions such as banks, asset management firms, and hedge funds, and they are increasingly adding courses in algorithms, machine learning, and other related areas to their education in order to understand this critical topic.
Career opportunities in this field are also attracting professionals with high-level computer science skills, who have gained nearly as high of a profile in the finance industry as algorithmic trading itself. Quantitative analysts, or “quants,” are highly prized for their ability to apply their programming skills to massive datasets, statistics, and other high-velocity market inputs to create the mathematical models required for algorithmic trading and other financial engineering techniques.
In a sense, then, algorithmic trading is where finance and programming meet, giving professionals with the ability to span these worlds the opportunity to create enormous value for their firms.