Quantitative Developer — Mid-Frequency Equity Statistical Arbitrage

Quantitative Developer — Mid-Frequency Equity Statistical Arbitrage Overview

We are seeking a Quantitative Developer to architect, implement, and maintain end-to-end production infrastructure supporting mid-frequency equity statistical arbitrage strategies. The role partners closely with researchers, traders, and operations to ensure research, back‑testing, and live‑trading systems are performant, reliable and operationally robust.

Key Responsibilities Architect, implement and maintain end-to-end production infrastructure for mid-frequency equity statistical arbitrage strategies. Develop and maintain research and back‑testing platforms. Design, own and operate analytics tools and UI to evaluate and monitor data, signal and trade quality and integrity. Ensure production systems are performant, reliable, observable and operationally robust. Continuously improve system design, scalability and operational resilience. Closely monitor production alpha generation, optimization and trading; raise and resolve issues with the highest efficiency to prevent potential P&L loss. Stay current on state‑of‑the‑art technologies and tools, including technical libraries, computing environments and relevant academic research. Requirements Minimum 3+ years of hands‑on quantitative development experience in an equity statistical‑arbitrage pod. Demonstrated experience in end‑to‑end development with direct responsibility for production trading infrastructure. Professional proficiency in Python and excellent coding practices. Strong familiarity with Snowflake and demonstrated proficiency in SQL to efficiently clean, transform and optimize large datasets. Experience with lightweight trader dashboard development. Experience with production monitoring, corporate action adjustment and a strong sense of operational priority. Familiarity with Optimizer a plus but not a must. Experience with building intraday system a plus. Clear understanding of the end‑to‑end equity systematic trading stack, including: Data ingestion, validation and normalization. Back‑testing and simulation. Portfolio construction and constraint enforcement. Live trading support. Strong engineering discipline and the ability to work independently with minimal guidance. Ability to adapt in a fast‑paced, collaborative, and results‑oriented environment; able to perform effectively under time‑sensitive and high‑pressure situations.

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