Quantitative Developer — Research Systems — Dallas

From Dallas, TX, the fully remote Quantitative Developer — Research Systems will build the research platform used to create reproducible market studies at scale. This opening is limited to applicants based in the Dallas, TX area and provides Central Time coordination of market-open decisions and cross-team risk review.

Compensation and Benefits

About the Role

In this Dallas, TX role, you will be accountable for research infrastructure, point-in-time data integrity, experiment lineage, and reliable numerical workloads while supporting Central Time coordination of market-open decisions and cross-team risk review. The work requires direct communication, explicit limits, and records that remain useful after market conditions change.

Dallas Operating Focus

The Dallas opening emphasizes measurable controls, prompt escalation, and reliable links between research and production. The operating day joins pre-market readiness, live risk review, and production follow-through. This opening must make cross-team decisions measurable by recording the trigger for escalation, the person who approved the response, and the condition that ends it. Routine work should be automated only after its failure behavior is understood. For this role, that means direct ownership of research-platform reliability, experiment lineage, and large time-series workloads during Central Time coordination of market-open decisions and cross-team risk review.

First Review Cycle

For the first complete work cycle in Dallas, TX, you will use Central Time coordination of market-open decisions and cross-team risk review to test how the team measures and escalates changes in research-platform reliability, experiment lineage, and large time-series workloads. The evidence package includes this task: Improve experiment tracking, lineage, and reproducibility. It also includes this task: Optimize large time-series workloads. The Dallas opening emphasizes measurable controls, prompt escalation, and reliable links between research and production. 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 research infrastructure, point-in-time data integrity, experiment lineage, and reliable numerical workloads without private context.

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 Central Time coordination of market-open decisions and cross-team risk review.

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 Dallas, TX 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 Dallas, TX 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.