Quantitative Developer — Research Systems — Boston

This Boston, MA-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 Eastern Time research challenge before the open and throughout the U.S. trading session.

Compensation and Benefits

About the Role

In this Boston, MA role, you will be accountable for research infrastructure, point-in-time data integrity, experiment lineage, and reliable numerical workloads while supporting Eastern Time research challenge before the open and throughout the U.S. trading session. The work requires direct communication, explicit limits, and records that remain useful after market conditions change.

Boston Operating Focus

The Boston opening emphasizes rigorous quantitative review, explicit uncertainty, and reproducible evidence. Independent challenge is built into the research schedule before any production decision. The opening must show how a conclusion changes under alternative samples, costs, and regimes. During live markets, deviations are recorded without forcing an immediate explanation, and later review determines whether the evidence supports a research or operating change. For this role, that means direct ownership of research-platform reliability, experiment lineage, and large time-series workloads during Eastern Time research challenge before the open and throughout the U.S. trading session.

First Review Cycle

The Boston, MA opening begins with an end-to-end review of research-platform reliability, experiment lineage, and large time-series workloads during Eastern Time research challenge before the open and throughout the U.S. trading session. The review will keep research observations separate from live production decisions. The evidence package includes this task: Improve experiment tracking, lineage, and reproducibility. It also includes this task: Optimize large time-series workloads. The Boston opening emphasizes rigorous quantitative review, explicit uncertainty, and reproducible evidence. A peer will review both results from the same source data. At the end of the cycle, you will show how the evidence supports or challenges research infrastructure, point-in-time data integrity, experiment lineage, and reliable numerical workloads. Open questions stay visible until another review resolves them.

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 Eastern Time research challenge before the open and throughout the U.S. trading 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 Boston, MA 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 Boston, MA 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.