ExodusPoint Capital, founded in 2017 by Michael Gelband and Hyung Lee, began managing investor capital in 2018. The firm employs a global multi-strategy investment approach, seeking to deliver compelling asymmetric returns by combining complementary liquid strategies managed by experienced investment professionals within a robust risk framework. ExodusPoint brings together an accomplished team with hands-on experience running multi-manager businesses to create an institutional investment management firm.
JOB DESCRIPTION
We are seeking a talented quantitative researcher to help build critical trading models and alpha signals. The role will be under the supervision of an existing portfolio manager in the fund and will be integral to increase both the breadth and depth of existing signals, as well as expanding into new signals/new markets.
Requirements:
- Prior research experience in an academic/industry setting involving computations/numerical analysis/computing/pattern recognition
- Ability to implement an hypothesis or idea into code
- Understanding of classical statistics, Bayesian statistics, optimization, numerical methods, data science
- Some familiarity with scientific methods and backtesting, strongly preferred
- Strong analytical and problem-solving skills, with the ability to process and interpret complex data
- Finance/economics background not required
Qualifications:
- Graduate degree at the Master’s/PhD level in a quantitative discipline
- 3 years of full time post graduation experience in quantitative finance
- Familiarity with Python, C/C++, Java, Solidity, SQL
- Alternative datasets such as consumer data (Experian, Dun and Bradstreet), commodities/weather related datasets, news/NLP sentiment, Satellite data
- Strong analytical skills, articulate, detail-oriented, curiosity to learn