Quantitative Researcher — Portfolio Construction — San Francisco

From San Francisco, CA, the fully remote Quantitative Researcher — Portfolio Construction will build portfolio methods that translate research signals into controlled exposures. This opening is limited to applicants based in the San Francisco, CA area and provides Pacific Time coverage of late-session behavior, system performance, and research handoffs.

Compensation and Benefits

Base salary: $185,000–$255,000 USD, based on experience
Work arrangement: Fully remote; applicants must be based in the San Francisco, CA area
Experience: 4+ years
Additional compensation: Performance-bonus and equity eligibility based on role and level

About the Role

The central responsibility of the San Francisco, CA opening is allocation methods, portfolio constraints, concentration limits, turnover controls, and stress diagnostics. The assigned window includes Pacific Time coverage of late-session behavior, system performance, and research handoffs. Success requires reproducible work, prompt escalation, and clear ownership through review and production use.

San Francisco Operating Focus

The San Francisco opening emphasizes strong quantitative engineering links and critical review before production change. The work combines quantitative review with production discipline during the final hours of the U.S. session. System behavior, data quality, and market evidence are assessed separately before a change is proposed. After the close, the opening prepares technical findings that Eastern Time colleagues can evaluate before the next market day. For this role, that means direct ownership of portfolio constraints, exposure diagnostics, and stress review during Pacific Time coverage of late-session behavior, system performance, and research handoffs.

First Review Cycle

For the first complete work cycle in San Francisco, CA, you will use Pacific Time coverage of late-session behavior, system performance, and research handoffs to test how the team measures and escalates changes in portfolio constraints, exposure diagnostics, and stress review. The first evidence set will cover this task: Model factor, sector, liquidity, and concentration constraints. The second will cover this task: Measure turnover, capacity, and stress behavior. The San Francisco opening emphasizes strong quantitative engineering links and critical review before production change. Each material deviation receives a named follow-up owner. At the end of the cycle, you will show how the evidence supports or challenges allocation methods, portfolio constraints, concentration limits, turnover controls, and stress diagnostics. Open questions stay visible until another review resolves them.

Responsibilities

• Develop allocation and risk-budgeting methods
• Model factor, sector, liquidity, and concentration constraints
• Measure turnover, capacity, and stress behavior
• Create transparent diagnostics for portfolio decisions
• Own portfolio constraints, exposure diagnostics, and stress review during Pacific Time coverage of late-session behavior, system performance, and research handoffs.

Required Qualifications

• Experience with portfolio optimization and risk models
• Strong numerical Python and optimization skills
• Ability to explain model tradeoffs to researchers and traders

Preferred Qualifications

• Experience with transaction-cost-aware optimization and scenario analysis
• Knowledge of production controls for constrained portfolios
• Experience collaborating across time zones while maintaining the operating coverage assigned to the San Francisco, CA opening.

Benefits

• Medical, dental, and vision plan options with substantial company support
• 401(k) plan with company matching
• Flexible paid time off and company holidaysPaid parental and caregiver leave
• Annual learning, conference, and professional-development budget
• Remote-work equipment and home-office support
• Performance-bonus and equity eligibility based on role and level

Benefits are subject to plan terms and eligibility requirements.

Equal Opportunity

Anemoi provides equal employment opportunities without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, or any other status protected by applicable law.