Quantitative Trader

Albert Bow Limited; New York (NY); Hybrid; USD 180,000 - 250,000; Full time

Job summary

Albert Bow Limited seeks a Quantitative/Algorithmic Trading Researcher for a remote or hybrid role focused on high-frequency strategy research across crypto and digital assets. You will design, test, and deploy production-ready trading algorithms and evaluate market dynamics in fast-moving environments.

The role requires hands-on coding with Rust or C, a track record of profitable strategy development, and comfort using AI tools within the development workflow.

Qualifications

• Experience in US equities, FX or crypto markets.
• Degree in a STEM field from a top university.
• Proven track record of building a profitable strategy from 0 to 1.
• Experience at a proprietary trading firm or hedge fund.
• Proficiency in Rust or C and use of AI tools in development workflow.

Responsibilities

• Conduct in-depth research on CeFi market data and order book dynamics.
• Design and deploy algorithmic trading strategies into production.
• Expand automated trading coverage into new products and venues, calibrating and tuning performance.
• Report on daily market sentiment, risk exposure, and P&L.
• Conduct post-trade analysis of strategy and algo performance, contributing to risk mitigation.

Skills

HFT experience

Algo trading

Market data research

Rust/C

AI tooling

Education

STEM degree

Tools

Rust

C

Job description

Quantitative/Algorithmic Trading Researcher — HFT Crypto & Digital Assets

Location: Remote or hybrid (US or APAC hub)

Our client is a full-stack, high-frequency proprietary trading firm with a global footprint across major financial centres in North America and Asia. The firm runs a proprietary, latency-sensitive trading system and execution platform, with direct access to major exchanges worldwide across multiple asset classes.

About the Role

You’ll apply quantitative and mathematical methods to evaluate financial products and markets, identifying trading opportunities and managing risk within a high-frequency, systematic trading environment.

Responsibilities

• Conduct in-depth research on CeFi market data and order book dynamics
• Design and deploy algorithmic trading strategies into production
• Expand automated trading coverage into new products and venues, calibrating and tuning performance
• Report on daily market sentiment, risk exposure, and P&L
• Conduct post-trade analysis of strategy and algo performance, contributing to risk mitigation and portfolio/strategy optimisation

Requirements

• Previous HFT experience in US equities, FX, or crypto markets
• STEM degree from a top university
• Track record of building a profitable strategy from 0 to 1 (need not be currently live)
• Focus on strategies with short holding periods, high trading frequency, and high turnover
• Prior experience at a proprietary trading firm or hedge fund
• Crypto experience a plus, not required
• Hands-on coding ability, ideally Rust or C , with comfort using AI tools in the development workflow

Process & General Info

• Remote or hybrid/on-site, depending on candidate preference and team fit
• Interview process includes 2–3 coding rounds, each 2–3 hours
• Excellent written and spoken English required; additional languages a plus