Quantitative Researcher — Systematic Equities — Albuquerque

The Albuquerque, NM opening for a Quantitative Researcher — Systematic Equities is fully remote and restricted to applicants in that area. Its mandate is to develop and test systematic equity research across sectors, factors, and changing market regimes while providing Mountain Time monitoring across both early-market and late-session operating windows.

Base salary: $175,000–$245,000 USD, based on experience
Work arrangement: Fully remote; applicants must be based in the Albuquerque, NM area
Experience: 3+ years
Additional compensation: Performance-bonus and equity eligibility based on role and level

In this Albuquerque, NM role, you will be accountable for a falsifiable research idea from point-in-time data construction through out-of-sample evaluation while supporting Mountain Time monitoring across both early-market and late-session operating windows. The work requires direct communication, explicit limits, and records that remain useful after market conditions change.

The Albuquerque opening emphasizes cross-time-zone continuity, unambiguous ownership, and measured incident response. Mountain Time coverage spans early national-market work and the later review window. The opening maintains continuity when responsibility moves between regions, with special attention to data timestamps and unfinished decisions. Incident response favors measured containment first, followed by analysis that can distinguish cause from correlation. For this role, that means direct ownership of equity-signal validation, sector diagnostics, and regime review during Mountain Time monitoring across both early-market and late-session operating windows.

In Albuquerque, NM, the first formal review will assess equity-signal validation, sector diagnostics, and regime review under the normal controls used for Mountain Time monitoring across both early-market and late-session operating windows. Any proposed response must remain within an approved limit. The evidence package includes this task:
Form hypotheses and build clean point-in-time equity datasets. It also includes this task:
Test signal stability, turnover, capacity, and transaction-cost sensitivity. The Albuquerque opening emphasizes cross-time-zone continuity, unambiguous ownership, and measured incident response. A peer will review both results from the same source data. The closing summary must show whether the evidence supports a change or only further study. It must let another specialist evaluate a falsifiable research idea from point-in-time data construction through out-of-sample evaluation without private context.

• Form 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 Mountain Time monitoring across both early-market and late-session operating windows.

• 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

• 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 Albuquerque, NM opening.

• 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.

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.