Quantitative Trader

Anson McCade; New York (NY); On-site; USD 150,000 - 200,000; Full time

Job summary

A leading proprietary trading firm is seeking a Senior High Frequency Futures Quantitative Trader to develop and scale algorithmic trading strategies. This high-impact role requires extensive experience in high-frequency trading and a strong quantitative background, offering competitive compensation and a collaborative environment.

Benefits

Access to proprietary technology

High level of autonomy

Supportive collaborative environment

Competitive compensation and incentives

Qualifications

• Minimum 5 years of experience in high-frequency trading focused on futures.
• Demonstrated success in developing profitable trading strategies.
• Experience with back-testing frameworks and simulation environments.

Responsibilities

• Research, design, and implement high-frequency systematic trading strategies.
• Collaborate with software engineers to optimize trading infrastructure.
• Analyze tick-level data to uncover market inefficiencies.

Skills

Quantitative Analysis

Statistical Models

Signal Generation

Risk Management

Coding in Python

Coding in C++

Education

MSc or PhD in Mathematics

MSc or PhD in Statistics

MSc or PhD in Computer Science

MSc or PhD in Physics

MSc or PhD in Engineering

Job description

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This range is provided by Anson McCade. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$150,000.00/yr - $200,000.00/yr

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Principal Headhunter - Quantitative Strategies at Anson McCade

Senior High Frequency Futures Quantitative Trader (New York/ London)

Company Overview

Our client is a leading proprietary trading firm specializing in high-frequency, cross-asset futures trading. Leveraging cutting-edge technology and a world-class infrastructure, they are expanding their trading capabilities and are looking for a seasoned quantitative trader to help develop and scale new algorithmic trading strategies in the futures space.

Role Overview

This is a high-impact role for an experienced quant trader with a proven track record in developing and deploying high-frequency systematic strategies. You will play a key role in the full lifecycle of strategy development, from idea generation to execution and optimization, supported by a strong team of developers and engineers.

Key Responsibilities

• Research, design, and implement high-frequency systematic trading strategies for futures markets
• Collaborate closely with software engineers to build, refine, and optimize trading infrastructure
• Identify and test new sources of alpha using proprietary and public datasets
• Analyze tick-level data to uncover inefficiencies and market patterns
• Develop tools for performance monitoring, data visualization, and signal analysis
• Continuously improve risk management, execution logic, and overall strategy performance

Required Experience & Skills

• Minimum 5 years of experience in high-frequency trading with a focus on futures
• MSc or PhD in a quantitative field (e.g., Mathematics, Statistics, Computer Science, Physics, or Engineering) from a top-tier institution
• Demonstrated success in independently developing and managing profitable trading strategies
• Deep understanding of statistical models, signal generation, and quantitative analysis
• Strong coding skills in Python and/or C++; experience working with large tick-level datasets
• Hands-on experience with back-testing frameworks, simulation environments, and production deployment
• Creative thinker with a passion for solving complex problems and uncovering new trading opportunities

Why Join?

• Access to cutting-edge proprietary technology and low-latency infrastructure
• High level of autonomy and ownership over strategy development
• Supportive, collaborative environment with highly experienced peers
• Competitive compensation and performance-based incentives

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Finance

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