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Investment banks recruit for rise of big data analytics

The investment banks are now looking at how they can use big data to do what they do better, faster and more efficiently. Senior executives at the banks want to enhance how they use data to raise profitability, map out markets and company-wide exposures, and ultimately win more deals. Big data is also a fundamental element of risk-profiling for the banks, enabling data analysts to immediately assess the impact of the escalation in geopolitical risk on portfolios and their exposure to specific markets and asset classes. Specifically, banks have now built systems that will map out market-shaping past events in order to identify future patterns. There lies the requirement of big data talent!

The banks are actively recruiting big data and analytics specialists to fill two main, but significantly different roles: big data engineers and data scientists. Data Scientists are responsible for bridging the gap between data analytics and business decision-making, capable of translating complex data into key strategy insight, while Data Engineers typically come from a strong IT development or coding background and are responsible for designing data platforms and applications. The competition between banks and fund managers to hire big data specialists is heating up. Data scientists are expected to have sharp technical and quantitative skills. They are in highest demand and this is where the biggest skill shortage exists.

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