Quantitative Trader

Albert Bow Limited; New York (NY); Remote; USD 213,000 - 288,000; Full time

Benefits offered by this job

Equity

PnL ownership

Remote work

Job summary

Albert Bow Limited in New York seeks an experienced Quantitative Trader to run and scale high-frequency trading strategies. You will own live PnL, develop ultra-low-latency trading signals, and collaborate with engineers to deploy and maintain production systems.

This role targets traders already running live strategies and ready to own a desk and grow it, with 2+ years of live PnL responsibility. Requirements include Python and at least one production language (C++, Rust, or Java), deep market

Qualifications

• Advanced degree (PhD/MSc) or strong BS in a quantitative field, or equivalent experience.
• 3+ years in HFT/market-making or equivalent low-latency trading experience.
• Proven track record trading live strategies.
• Strong Python and at least one production language (C++, Rust, Java).
• Deep knowledge of market microstructure, order books, execution, and latency.
• Experience with tick-level data, backtesting frameworks, and live monitoring.
• Strong statistics, time-series, and risk-management skills.

Responsibilities

• Own live trading strategies, PnL, and risk across multiple venues.
• Develop and refine microstructure-aware alpha and execution tactics.
• Implement and iterate low-latency signal and execution improvements with engineers.
• Design and validate realistic backtests (market impact, latency) and monitor live performance and risk.
• Maintain reproducible deployment pipelines, data quality checks, and monitoring.

Skills

Python

C++

Rust

Java

Statistics

Time-series

Risk management

Education

PhD

MSc

BS in quantitative field

Tools

Backtesting frameworks

Live monitoring

Data feeds

Cloud/on-prem infra

Job description

Quantitative Trader | MFT/HFT | New York (Remote for top applicants) $250k + PnL

We’re seeking an experienced Quantitative Trader to run and scale HFT strategies. You will own live PnL, develop and refine ultra-low-latency trading signals, and work with engineers to deploy and maintain production systems.

Why this is different The firm wants traders already running live strategies who are ready to move to their own desk and grow it, not run-of-the-mill candidates.

2+ years trading live strategies with demonstrable PnL responsibility.

Key Responsibilities

• Own live trading strategies, PnL, and risk across multiple venues.
• Develop and refine microstructure-aware alpha and execution tactics.
• Implement and iterate low-latency signal and execution improvements with engineers.
• Design and validate realistic backtests (market impact, latency) and monitor live performance and risk.
• Maintain reproducible deployment pipelines, data quality checks, and monitoring.

Required Qualifications

• Advanced degree (PhD/MSc) or strong BS in a quantitative field, or equivalent experience.
• 3+ years in HFT/market-making or equivalent low-latency trading experience.
• Proven track record trading live strategies.
• Strong Python and at least one production language (C++, Rust, Java).
• Deep knowledge of market microstructure, order books, execution, and latency.
• Experience with tick-level data, backtesting frameworks, and live monitoring.
• Strong statistics, time-series, and risk-management skills.

Preferred Qualifications

• Prior experience building or leading a desk.
• Experience with automated deployment, cloud/on-prem infrastructure, real-time feeds, and message buses.
• Familiarity with reinforcement learning or advanced ML applied to trading.

What We Offer

• Competitive compensation: $250k + PnL + equity.
• Ownership of desk strategy and fast career progression.
• Access to high-quality market data and best-in-class infrastructure.