Quantitative Developer — Research Systems — Milwaukee

This Milwaukee, WI-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 Central Time coverage that connects morning preparation with afternoon validation.

Compensation and Benefits

About the Role

The central responsibility of the Milwaukee, WI opening is research infrastructure, point-in-time data integrity, experiment lineage, and reliable numerical workloads. The assigned window includes Central Time coverage that connects morning preparation with afternoon validation. Success requires reproducible work, prompt escalation, and clear ownership through review and production use.

Milwaukee Operating Focus

The Milwaukee opening emphasizes stable daily processes, careful measurement, and practical collaboration across functions. The working schedule pairs morning preparation with an afternoon validation block. This makes it possible to compare what the team expected with what production and markets actually did. The opening converts that difference into a small, prioritized improvement list rather than allowing recurring issues to remain informal knowledge. For this role, that means direct ownership of research-platform reliability, experiment lineage, and large time-series workloads during Central Time coverage that connects morning preparation with afternoon validation.

First Review Cycle

The first review cycle for Milwaukee, WI starts with Central Time coverage that connects morning preparation with afternoon validation. 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 evidence package includes this task: Add tests that detect leakage and inconsistent data vintages. It also includes this task: Develop reusable data and backtest infrastructure. The Milwaukee opening emphasizes stable daily processes, careful measurement, and practical collaboration across functions. A peer will review both results from the same source data. The review is complete when a peer can reproduce the evidence, inspect the decision limit, and trace the outcome through 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 Central Time coverage that connects morning preparation with afternoon validation.

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 Milwaukee, WI 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 Milwaukee, WI 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.