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Principal Quantitative Researcher – Applied AI & Portfolio Systems – San Francisco, California
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Principal Quantitative Researcher – Applied AI & Portfolio Systems – San Francisco, California
An early-stage technology company is building a new generation of quantitative systems for long-horizon investing. The focus is on replacing fragmented, manual decision-making with algorithmic, data-driven portfolio construction that scales across clients while respecting real-world constraints.
This role is for a senior quantitative researcher who wants end-to-end ownership: from mathematical formulation and modeling through to production deployment and real-world feedback.
What You’ll Own
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Design and implementation of portfolio construction algorithms incorporating risk, return, constraints, and after-tax considerations
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Development of machine learning models that adapt portfolio decisions to heterogeneous client objectives and behaviors
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Core quantitative research that underpins model-driven recommendations across the platform
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Translation of practitioner constraints into mathematically tractable models through direct interaction with end users
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Continuous iteration on models based on empirical performance, feedback loops, and new data sources
Seniority & Background
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Significant experience as a quantitative researcher in a high-caliber investment or research environment
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Roughly 7+ years of industry experience, or fewer years combined with a strong advanced degree and demonstrated applied impact
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Track record of designing, implementing, and deploying quantitative strategies or models (not purely conceptual work)
Quantitative & Technical Strengths
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Deep experience in one or more of: portfolio optimization, risk modeling, systematic investment strategies, or asset allocation
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Strong foundations in statistical modeling, optimization, and numerical methods
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Comfortable working across the full modeling stack, from research code to production systems
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Strong interest in modern AI techniques and their application to decision-making systems
Education
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PhD or equivalent depth of training in a quantitative field such as finance, mathematics, economics, physics, or computer science is strongly preferred, unless offset by substantial applied experience
Operating Style
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Thrives in small, fast-moving environments with minimal hierarchy
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Motivated by ownership and problem-solving rather than people management
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Comfortable mentoring others while remaining a hands-on individual contributor
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Strong communication skills and product intuition, with the ability to explain technical decisions to non-technical stakeholders
This Role Is Not For
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Candidates focused primarily on strategy, management, or organizational leadership
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Researchers without experience translating models into real systems
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Profiles centered exclusively on discretionary trading without a research foundation
This job was published by Barclay Simpson: https://www.barclaysimpson.com/job/principal-quantitative-researcher-applied-ai-portfolio-systems-san-francisco-california/
We seek individuals from a diverse talent pool and encourage applicants from underrepresented groups to apply to our vacancies. Our commitment to fair recruitment processes means that we welcome applicants from all backgrounds, regardless of their lived experience or personal characteristics. We also invite applicants who meet most of the listed requirements, even if not all, to apply. If you require any adjustments to the application process, please let us know.
Barclay Simpson acts as an Employment Agency for permanent positions and an Employment Business for temporary/contract engagements.
