Evan Chow

Evan Chow

Quantitative researcher & data scientist at ADIA, the sovereign wealth fund of Abu Dhabi. Formerly @ Snap, Uber, Princeton, LSE. All views are mine.

Welcome!

It’s great to meet you, and thanks for swinging by. I’m Evan.

  • quantitative researcher at the Abu Dhabi Investment Authority (ADIA), previously in tech
  • lifelong classical & jazz pianist, and amateur producer: Spotify
  • originally from the San Francisco Bay Area, but lived in various places

Here you can find my informal explorations into quantitative sciences, music, and more. Enjoy!

Warm regards,
Evan

music-math

My current position

Risk.net - Adia wealth fund is building supergroup of quant investing

I work as a quantitative researcher at ADIA: this spans the full range from research prototypes to final production pipelines for quantitative investments.

  • Data science: sourcing datasets (financial and alternative), evaluating potential investment alpha
  • Signal development: statistical analyses on data, developing useful features and signals
  • Portfolio optimization: constructing and optimizing investment portfolios
  • Seminars: developing, analyzing and presenting strategies to the wider group for feedback
  • Production: building and monitoring production data pipelines, monitoring anomalies and investigating outages

Domain. I focus on industrial economics, transportation, and complex networks. I have also contributed to other systematic/semi-systematic work involving a variety of useful alternative data.

Teaching. Since my role is within a scientific investing team, I have also run a number of industry-academic projects via ADIA Lab, the scientific institution of ADIA. These have primarily been in the form of MSc-level capstone projects, and some examples include:

  • UCL/Oxford (MSc MCF): Nowcasting global trade with time series signatures & shipping data (2024)
  • University of Toronto (MFRM): Nowcasting inflation with the Baltic indices (2023)
  • Khalifa University (MSc Data Science): Studies in supply chains, institutional ownership and geographic revenue (2022)

You can see the full list here: Teaching

Before quantitative finance

Previously in the technology sector, I worked as a data scientist and research scientist at Snap Inc. (2017-2020), primarily on causal inference and econometric analysis to drive product and engineering strategy. Before that I worked briefly at Uber (2016-2017) on optimal driver-rider matching algorithms and engineering.

I studied the MSc EME program at the London School of Economics, and before that an undergrad in economics, statistics & machine learning at Princeton.

Other

I am a lifelong classically trained musician (classical and jazz pianist) and so you may also find quant-music explorations here.

Disclaimer: The views expressed on this personal website are mine and do not necessarily reflect the official policy or position of any institutions I am affiliated with or have been affiliated with.