Remote Quantitative Developer – Research Systems (KC)

Anemoi Predictive Technology LLC.; Kansas City (MO); 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 companyhol

Paid parental and caregiver leave

Annual learning and development budget

Remote-work equipment and home-office

Performance-bonus and equity eligible

Job summary

Anemoi Predictive Technology LLC is seeking a Quantitative Developer — Research Systems in Kansas City, MO. The role focuses on building a scalable research platform for reproducible market studies, with Central Time oversight accompanying morning reviews and live-market supervision.

You will own research infrastructure, data lineage, and large time-series workloads, while collaborating with quantitative researchers and ensuring data integrity in a fully remote arrangement based in the KC area.

Qualifications

• Production-grade Python and SQL experience.
• Strong knowledge of distributed data systems and numerical workloads.
• Experience supporting quantitative researchers.
• Experience coordinating across time zones.

Responsibilities

• Develop reusable data and backtest infrastructure.
• Improve experiment tracking, lineage, and reproducibility.
• Optimize large time-series workloads.
• Add tests for leakage and data vintages.
• Own research-platform reliability during Central Time oversight that joins morning research review with live-market supervision.

Skills

Python

SQL

Distributed data

Researchers support

Time-zone collaboration

Tools

Workflow orchestration

Cloud environments

Columnar data

Job description

Anemoi Predictive Technology LLC is seeking a Quantitative Developer — Research Systems in Kansas City, MO. The role focuses on building a scalable research platform for reproducible market studies, with Central Time oversight accompanying morning reviews and live-market supervision.

You will own research infrastructure, data lineage, and large time-series workloads, while collaborating with quantitative researchers and ensuring data integrity in a fully remote arrangement based in the KC area.