Quantitative Developer — Research Systems — Kansas

This Kansas City, MO-based, fully remote Quantitative Developer — Research Systems position will build the research platform used to create reproducible market studies licants must live in the local area, which gives the team Central Time oversight that joins morning research review with live-market supervision.

• Base salary: $185,000-$260,000 USD, based on experience
• Work arrangement: Fully remote; applicants must be based in the Kansas City, MO area
• Experience: 4+ years
• Additional compensation: Performance-bonus and equity eligibility based on role and level

In this Kansas City, MO role, you will be accountable for research infrastructure, point-in-time data integrity, experiment lineage, and reliable numerical workloads while supporting Central Time oversight that joins morning research review with live-market supervision. The work requires direct communication, explicit limits, and records that remain useful after market conditions change.

The Kansas City opening emphasizes balanced decision timing, explicit controls, and reliable research-to-trading transfer. The Central Time schedule provides room for both morning research challenge and full live-session supervision. This opening decides when new evidence is strong enough to require escalation and when observation should continue. Research-to-trading transfers name the intended use, limit, monitoring plan, and condition that ends the experiment.

For this role, that means direct ownership of research-platform reliability, experiment lineage, and large time-series workloads during Central Time oversight that joins morning research review with live-market supervision.

The first review cycle for Kansas City, MO starts with Central Time oversight that joins morning research review with live-market supervision. It will establish a measured baseline for research-platform reliability, experiment lineage, and large time-series workloads before the team proposes an operating change. The operating test starts with this task:
Improve experiment tracking, lineage, and reproducibility. It continues with this task:
Optimize large time-series workloads. The Kansas City opening emphasizes balanced decision timing, explicit controls, and reliable research-to-trading transfer. The findings must distinguish confirmed evidence from an early explanation. 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.

• 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 oversight that joins morning research review with live-market supervision.

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

• 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 Kansas City, MO 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.