Trading Operations / Quant Hedge Fund

Alexander Chapman Ltd; New York (NY); Hybrid; USD 180,000 - 220,000; Full time

Benefits offered by this job

Relocation provided

Comprehensive premium benefits

401(k) match

Sign-on package

Job summary

Alexander Chapman Ltd in New York is seeking a Member of Trading Operations to oversee end-to-end trade lifecycle management, real-time position integrity, and trade capture across global markets. You will build Python and SQL automation tools, work with systematic trading desks, researchers, and engineers, and support seamless trade flow with strong process discipline in a hybrid NYC setting.

This role offers a highly competitive first-year package with base and total compensation,

Qualifications

• 1 to 6 years in Trade Operations, Trade Support, or Middle Office within a proprietary trading firm, market maker, or quantitative fund.
• Production-level Python and SQL skills with proven capability to architect and deploy custom automation tools.
• Deep working knowledge of trade lifecycle mechanics, execution pipelines, and multi-asset clearing and settlement reconciliations.
• A technical educational background, ideally holding a degree in Computer Science, Data Science, Mathematics, Statistics, Econometrics, or a closely related quantitative/mathematical field.

Responsibilities

• Oversee end-to-end trade lifecycle management, real-time position integrity, and trade capture across global markets and exchange venues.
• Rapidly identify and resolve live trading breaks, execution discrepancies, and post-trade operational issues during market hours.
• Build and optimize custom Python and SQL tools to automate manual workflows, position checks, and daily reconciliation processes.
• Collaborate directly with systematic trading desks & traders directly, quantitative researchers, software engineers, and external counterparties to ensure seamless trade flow and operational resilience.

Skills

Python

SQL

Trade lifecycle knowledge

Automation tooling

Education

CS/Math/Data Science degree

Quantitative background

Job description

I am running an exclusive search for a very secretive $40B+ systematic quantitative hedge fund in New York. Recognized globally for market-leading latency and algorithmic alpha, the firm operates at the absolute cutting edge of mathematical finance, technology, and proprietary automated execution.

We are hiring a Member of Trading Operations, this position is not public.

Responsibilities

• Oversee end-to-end trade lifecycle management, real-time position integrity, and trade capture across global markets and exchange venues.
• Rapidly identify and resolve live trading breaks, execution discrepancies, and post-trade operational issues during market hours.
• Build and optimize custom Python and SQL tools to automate manual workflows, position checks, and daily reconciliation processes.
• Collaborate directly with systematic trading desks & traders directly, quantitative researchers, software engineers, and external counterparties to ensure seamless trade flow and operational resilience.

You are a fit if you meet the following:

• 1 to 6 years in Trade Operations, Trade Support, or Middle Office within a proprietary trading firm, market maker, or quantitative fund.
• Production-level Python and SQL skills with proven capability to architect and deploy custom automation tools.
• Deep working knowledge of trade lifecycle mechanics, execution pipelines, and multi-asset clearing and settlement reconciliations.
• A technical educational background, ideally holding a degree in Computer Science, Data Science, Mathematics, Statistics, Econometrics, or a closely related quantitative/mathematical field.

HFT background strongly preferred. Non-compete agreements are respected and bought out.

• First-Year Compensation: $180,000 - $220,000 Base / $280,000 - $340,000 Total Compensation (Base + Discretionary Performance Bonus + Sign-on Package on-top). Comprehensive premium benefits and 401(k) match.
• Location: New York, NY (Hybrid). Full relocation provided, including several months of corporate housing fully paid for by the firm.