Quantitative Developer — Research Systems — New York

This New York, NY-based, fully remote Quantitative Developer — Research Systems position will build the research platform used to create reproducible market studies at scale. Applicants must live in the local area, which gives the team early U.S. market preparation and the full Eastern Time cash session.

Compensation and Benefits

About the Role

In this New York, NY role, you will be accountable for research infrastructure, point-in-time data integrity, experiment lineage, and reliable numerical workloads while supporting early U.S. market preparation and the full Eastern Time cash session. The work requires direct communication, explicit limits, and records that remain useful after market conditions change.

New York Operating Focus

The New York opening emphasizes fast morning escalation, precise market-open review, and complete end-of-day records. Daily work begins before the cash open with overnight-gap review, scheduled-event checks, and clear escalation ownership. Opening and closing auctions receive separate analysis because each can create different liquidity and execution conditions. Post-close records must explain what changed, what remained uncertain, and which issue carries into the next session. For this role, that means direct ownership of research-platform reliability, experiment lineage, and large time-series workloads during early U.S. market preparation and the full Eastern Time cash session.

First Review Cycle

In New York, NY, the first formal review will assess research-platform reliability, experiment lineage, and large time-series workloads under the normal controls used for early U.S. market preparation and the full Eastern Time cash session. Any proposed response must remain within an approved limit. The operating test starts with this task: Improve experiment tracking, lineage, and reproducibility. It continues with this task: Optimize large time-series workloads. The New York opening emphasizes fast morning escalation, precise market-open review, and complete end-of-day records. The findings must distinguish confirmed evidence from an early explanation. Completion requires a repeatable evidence path, a clear response boundary, and a time for the next check. Those records must connect directly to research infrastructure, point-in-time data integrity, experiment lineage, and reliable numerical workloads.

Responsibilities

• Develop reusable data and backtest infrastructure
• Improve experiment tracking, lineage, and reproducibility
• Optimize large time-series workloads
• Add tests that detect leakage and inconsistent data vintages
• Own research-platform reliability, experiment lineage, and large time-series workloads during early U.S. market preparation and the full Eastern Time cash session.

Required Qualifications

• Production Python and SQL experience
• Strong knowledge of distributed data systems and numerical workloads
• Experience supporting quantitative researchers

Preferred Qualifications

• Experience with workflow orchestration, columnar data, and cloud research environments
• A record of improving speed without weakening correctness or auditability
• Experience collaborating across time zones while maintaining the operating coverage assigned to the New York, NY 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 New York, NY 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.