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Mao Ching Foo: Running Quant Funds, Data Science & IQ vs. EQ

· Podcast Episodes,Founder,Singapore,Data Science,IQ vs EQ

In terms of staffing or managingpeople, my approach has always been that of you have to empathize with what the other person is, with what he's doing, what is going on in his background whether it's family issues that come to work or whatnot, right? You help him compartmentalize and you try to help him perform. EQ definitely plays a part as much as the IQ side. So I mean it's a blend of both. And it's really acase by case basis in terms of if you have workers with different issues but by and large, the team is as mall team one where everybody is performing pretty well. So it's performance-driven, a lot of accountability, processes that govern our work so it's quite clear.  - Mao Ching Foo

Mao Ching Foo is the Co-Founder at RealVantage, a property co-investment platform bringing access and enables users to easily own investment grade properties without the traditional hassles of being a landlord.

Previously Mao was the CTO & Chief Data Scientist of Funding Societies | Modalku, leading and growing the technology and data teams while working closely with the business teams to scale the platform for users. Prior to Funding Societies, Mao founded QVantage, a startup empowering equity traders to make smarter decisions using professional quantitative insights. He has also served as Chief Data Scientist of Paktor, a technology startup with presence in 8 countries in the region, and over 5 million users. In this role, he set up the full data science infrastructure and pipelines, built up a team of data analysts, scientists and conducted various studies / models to advance Product & Marketing metrics lift.

Before the world of startups, Mao was a quantitative equities trader / portfolio manager in Barclays Global Investors in San Francisco, and subsequently at Ronin Capital, a proprietary trading firm in Chicago. In these roles, he managed all aspects of a market neutral quantitative equities long-short global portfolio. This included researching alpha signals, constructing country specific Barra-type daily risk models, automatic sub-hourly portfolio optimizations, automatic trade execution algos & T-Cost analysis. Trade execution was through a Java OMS on FIX connectivity to DMA destinations. Market exposure was 100 x 100 mio long short with consistent after cost IR performance of 2+ on the overall global portfolio.

Mao graduated from Stanford with a MSc. and a MComp, BComp Hons in Computer Science from National University of Singapore. He has publications in top ranked journals, refereed conferences and book chapters. He is a strong believer of building technology startup ecosystems and is an angel investor and mentor to several startups in the region.

This episode is produced by Kyle Ong.

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