Remote Quantitative Researcher, Systematic Equities

Anemoi Predictive Technology LLC.; Washington; Hybrid; USD 175,000 - 245,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k) matching

Flexible paid time off

Parental leave

Learning budget

Remote-work equipment

Performance-bonus and equity

Job summary

The Washington, DC-based opening is for a fully remote Quantitative Researcher focusing on systematic equities. You will develop and test research across sectors and changing market regimes, with Eastern Time monitoring and policy-sensitive sessions.

You will own equity-signal validation, run walk-forward and out-of-sample evaluation, and present results to the investment team. The role requires 3+ years of quantitative experience, Python and SQL proficiency, and a track record of reproducible

Qualifications

• Three or more years in quantitative research, data science, or systematic investing.
• Proficiency in Python and SQL with strong probability and statistics.
• Clear understanding of backtest bias and model validation.

Responsibilities

• Form hypotheses and build 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 Eastern Time monitoring and reviews.

Skills

Python

SQL

Quantitative research

Backtest bias understanding

Job description

This Washington, DC-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 Eastern Time monitoring of market events, policy-sensitive sessions, and close review.

Compensation and Benefits

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

About the Role

The central responsibility of the Washington, DC opening is a falsifiable research idea from point-in-time data construction through out-of-sample evaluation. The assigned window includes Eastern Time monitoring of market events, policy-sensitive sessions, and close review. Success requires reproducible work, prompt escalation, and clear ownership through review and production use.

Washington Operating Focus

The Washington opening emphasizes careful treatment of event risk, source quality, and documented decision limits. Scheduled policy events and unexpected public announcements can change market conditions quickly. This opening verifies source timing, separates confirmed information from interpretation, and avoids treating a headline as proof of a durable regime. Event procedures define exposure checks, communication order, and the point when normal operations resume. For this role, that means direct ownership of equity-signal validation, sector diagnostics, and regime review during Eastern Time monitoring of market events, policy-sensitive sessions, and close review.

First Review Cycle

Your first documented cycle for the Washington, DC opening will test the operating process for equity-signal validation, sector diagnostics, and regime review during Eastern Time monitoring of market events, policy-sensitive sessions, and close review. The objective is a reproducible baseline, not a quick narrative. The evidence package includes this task: Run walk-forward and out-of-sample evaluation. It also includes this task: Present both favorable and unfavorable results to the investment team. The Washington opening emphasizes careful treatment of event risk, source quality, and documented decision limits. A peer will review both results from the same source data. The cycle ends with a short decision record, its limit, the next check, and each unresolved question. Another specialist must be able to trace the work through a falsifiable research idea from point-in-time data construction through out-of-sample evaluation.

Responsibilities

• 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 Eastern Time monitoring of market events, policy-sensitive sessions, and close review.

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 Washington, DC 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.

How to Apply

Submit a current resume through the application form for the Washington, DC opening. A short cover letter is optional. We will contact qualified applicants about the interview process and next steps.

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.