Remote Quantitative Developer — Research Systems

Anemoi Predictive Technology LLC.; Colorado Springs (CO); Remote; USD 185,000 - 260,000; Full time

Benefits offered by this job

Medical, dental, and vision plan

401(k) plan with company matching

Flexible paid time off and companyholi

Paid parental and caregiver leave

Annual learning, conference, and pro‑f

Remote-work equipment and home-office

Performance-bonus and equity eligible

Job summary

Anemoi Predictive Technology LLC is seeking a fully remote Quantitative Developer — Research Systems based in the Colorado Springs, CO area to build the research platform used to create reproducible market studies at scale. The role covers Mountain Time hours, including pre-market preparation, the cash session, and late review.

You will own research infrastructure, data integrity, experiment lineage, and large time-series workloads, collaborating with a small team of specialists and ensuring

Qualifications

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

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 Mountain Time coverage spanning early preparation, the cash session, and late review.

Skills

Python

SQL

Distributed data systems

Numerical workloads

Tools

Airflow

Job description

Anemoi Predictive Technology LLC is seeking a fully remote Quantitative Developer — Research Systems based in the Colorado Springs, CO area to build the research platform used to create reproducible market studies at scale. The role covers Mountain Time hours, including pre-market preparation, the cash session, and late review.

You will own research infrastructure, data integrity, experiment lineage, and large time-series workloads, collaborating with a small team of specialists and ensuring