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Job Description
What qualifications, skills and traits should you possess in this role?
•Advanced degree in Mathematics, Statistics, Financial Engineering, Computer Science, or related quantitative field
•5-12 years of experience in asset management, including time as a risk-taker or as a quantitative strategist working in close partnership with fundamental portfolio managers
•Demonstrated track record of contributing to investment decisions in fundamental equity strategies, whether as a decision-maker with P&L responsibility or as a quant partner whose work directly shaped portfolio outcomes
•Deep expertise in portfolio construction, attribution, and risk modelling for fundamentally driven equity portfolios. Comfortable working with both statistical and fundamental inputs when shaping positions.
•Fluent in how fundamental investors think and decide (valuation methods, idea generation, thesis development, catalyst identification), even if your own background is quantitative
•High proficiency in Python and statistical/data analysis libraries
•Sound investment judgment under uncertainty, decisive under incomplete information, with strong risk discipline and intellectual honesty in evaluating losses.
•Strong collaborator, comfortable working in a team portfolio structure alongside fellow PMs and AI engineers, and willing to operate in the ambiguity of an early-stage team.
•Genuine interest in generative AI and how it can be applied to fundamental investing.
•Advanced degree in Mathematics, Statistics, Financial Engineering, Computer Science, or related quantitative field
•5-12 years of experience in asset management, including time as a risk-taker or as a quantitative strategist working in close partnership with fundamental portfolio managers
•Demonstrated track record of contributing to investment decisions in fundamental equity strategies, whether as a decision-maker with P&L responsibility or as a quant partner whose work directly shaped portfolio outcomes
•Deep expertise in portfolio construction, attribution, and risk modelling for fundamentally driven equity portfolios. Comfortable working with both statistical and fundamental inputs when shaping positions.
•Fluent in how fundamental investors think and decide (valuation methods, idea generation, thesis development, catalyst identification), even if your own background is quantitative
•High proficiency in Python and statistical/data analysis libraries
•Sound investment judgment under uncertainty, decisive under incomplete information, with strong risk discipline and intellectual honesty in evaluating losses.
•Strong collaborator, comfortable working in a team portfolio structure alongside fellow PMs and AI engineers, and willing to operate in the ambiguity of an early-stage team.
•Genuine interest in generative AI and how it can be applied to fundamental investing.