Quantitative Researcher — Systematic Equities — Portland

This Portland, OR-based, fully remote Quantitative Researcher — Systematic Equities position will develop and test systematic equity research across sectors, factors, and changing market regimes. Applicants must live in the local area, which gives the team Pacific Time supervision of late-session behavior and asynchronous research delivery.

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

In this Portland, OR role, you will be accountable for a falsifiable research idea from point-in-time data construction through out-of-sample evaluation while supporting Pacific Time supervision of late-session behavior and asynchronous research delivery. The work requires direct communication, explicit limits, and records that remain useful after market conditions change.

The Portland opening emphasizes thoughtful written review, durable remote collaboration, and careful production change. Much of the collaboration is asynchronous, so written work must explain the question, method, evidence, and limitation without relying on verbal context. Pacific Time coverage includes the market close and later validation. A proposed production change is not ready until another specialist can reproduce the result and challenge its assumptions.

For this role, that means direct ownership of equity-signal validation, sector diagnostics, and regime review during Pacific Time supervision of late-session behavior and asynchronous research delivery.

Your first documented cycle for the Portland, OR opening will test the operating process for equity-signal validation, sector diagnostics, and regime review during Pacific Time supervision of late-session behavior and asynchronous research delivery. The objective is a reproducible baseline, not a quick narrative. The operating test starts with this task:
Form hypotheses and build clean point-in-time equity datasets. It continues with this task:
Test signal stability, turnover, capacity, and transaction-cost sensitivity. The Portland opening emphasizes thoughtful written review, durable remote collaboration, and careful production change. The findings must distinguish confirmed evidence from an early explanation. Before the review closes, you will state what changed, what did not change, and what needs more evidence. A peer must be able to follow the result back to a falsifiable research idea from point-in-time data construction through out-of-sample evaluation.

• 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 Pacific Time supervision of late-session behavior and asynchronous research delivery.

• 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 Portland, OR 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.