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Hedge fund Delphia hires Amazon’s lead scientist, reports record performance

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Delphia, an investment adviser that rewards investors for sharing data to improve their returns, has appointed Andrew Arnold as chief science officer. The company’s hedge fund has also disclosed an average 72% net return in its first year of performance (59% net return to those paying the highest fees).

Delphia, an investment adviser that rewards investors for sharing data to improve their returns, has appointed Andrew Arnold as chief science officer. The company’s hedge fund has also disclosed an average 72% net return in its first year of performance (59% net return to those paying the highest fees).

As the lead scientist on AWS’ (Amazon Web Services) CodeWhisperer, Arnold is a proven expert in machine learning and artificial intelligence. With its proprietary prediction models and quantitative investment approach, Delphia has the fifth highest-performing equity long-short fund, by single-year performance, in hedge fund history. With Arnold’s addition to the team, the Company is doubling down on the combination of AI and proprietary data as a way to continuously outperform the market and previous industry benchmarks.

Arnold will build on top of Delphia’s existing proprietary prediction models and quantitative investment framework to surface new insights and discoveries from the Company’s vast and growing data set, adding to Delphia’s already impressive performance. Through Arnold’s contributions, Delphia will continue to improve upon its stock selection model at an ever-increasing pace, providing a greater chance for accredited and non-accredited investors alike to take advantage of future investment opportunities.

Prior to joining Delphia, Arnold led a team of applied researchers and scientists at AWS, where the team launched CodeWhisperer, an AI pair programming tool, similar to GitHub’s Copilot, that can autocomplete entire functions based on only a comment or a few keystrokes. Before that, Arnold held various leadership positions at prominent global organisations in the fields of machine learning, artificial intelligence, and quantitative trading. Arnold holds a PhD in Machine Learning from Carnegie Mellon University and a BA in Computer Science and Artificial Intelligence from Columbia University. He is also an Adjunct Professor in NYU’s Department of Finance and Risk Engineering, where he lectures on natural language processing and machine learning applied to quantitative trading and finance.

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