Quantitative Researcher — Systematic Equities — San Francisco

Work arrangement: Fully remote; applicants must be based in the San Francisco, CA area

Experience: 3+ years Additional compensation: Performance-bonus and equity eligibility based on role and level

About the Role: This opening gives the San Francisco, CA hire responsibility for a falsifiable research idea from point-in-time data construction through out-of-sample evaluation, with operating coverage focused on Pacific Time coverage of late-session behavior, system performance, and research handoffs. You will connect research, engineering, trading, and risk without hiding uncertainty or operational tradeoffs. San Francisco Operating FocusThe 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 equity-signal validation, sector diagnostics, and regime review during Pacific Time coverage of late-session behavior, system performance, and research handoffs. First Review CycleThe San Francisco, CA opening begins with an end-to-end review of equity-signal validation, sector diagnostics, and regime review during Pacific Time coverage of late-session behavior, system performance, and research handoffs. The review will keep research observations separate from live production decisions. One required check is: Test signal stability, turnover, capacity, and transaction-cost sensitivity. The next required check is: Run walk-forward and out-of-sample evaluation. The San Francisco opening emphasizes strong quantitative engineering links and critical review before production change. You will identify any assumption that remains untested after both checks. The final note will connect the outcome to a falsifiable research idea from point-in-time data construction through out-of-sample evaluation and give another specialist enough detail to challenge the decision without a separate meeting. ResponsibilitiesForm hypotheses and build clean point-in-time equity datasets Test signal stability, turnover, capacity, and transaction-cost sensitivity Run walk-forward and out-of-sample evaluation Present both favorable and unfavorable results to the investment team Own equity-signal validation, sector diagnostics, and regime review during Pacific Time coverage of late-session behavior, system performance, and research handoffs.

Required Qualifications: Three or more years in quantitative research, data science, or systematic investing Python and SQL proficiency with strong probability and statistics Clear understanding of backtest bias and model validation

Preferred Qualifications: Experience with equity factors, corporate actions, and point-in-time fundamentals A record of moving research into monitored production use 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 holidays Paid 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 OpportunityAnemoi 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.