Prop mm quant trader

KOS International Talent Group; United States; Presencial; USD 140.000 - 210.000; Jornada completa

Descripción de la vacante

KOS International Talent Group is partnering with a market-making firm to recruit a Quantitative Market Making Trader. The role focuses on live operation, data analysis, and optimization of market-making strategies across digital asset spot and derivatives markets.

The position combines live strategy execution with quantitative research, requiring collaboration with engineering to continuously improve profitability and market competitiveness in fast-paced environments.

Formación

• Bachelor's degree or higher in CS/Math/Statistics/Financial Engineering or related field.
• Strong understanding of digital asset spot and derivatives markets and their trading mechanisms.
• Strong understanding of order books, matching engines, and market microstructure.
• Proficiency in Python for data analysis, strategy validation, and automation tools.
• Familiarity with Linux, SQL, Git and related development tools.
• Strong data analysis skills to identify issues from trading data and develop solutions.
• Strong analytical and logical thinking with a continuous improvement mindset.

Responsabilidades

• Operate and monitor high-frequency market-making strategies daily, tracking performance and risk metrics.
• Identify and resolve trading issues, including data anomalies, order issues, execution issues, and risk-control events.
• Analyze live strategy performance and drive improvements and issue resolution.
• Collaborate with the engineering team to deploy new strategies and improve the trading system.
• Research and optimize strategy parameters to reduce losses from adverse selection.
• Study market microstructure and optimize quote placement, inventory management, and risk controls.
• Use historical and live data to improve key metrics like PnL and quote lifetime.

Conocimientos

Analytical thinking

Ownership mindset

Problem solving

Educación

Bachelor's degree or higher in CS/Math/Statistics/Financial Engineering or related field

Herramientas

Python

Linux

SQL

Git

Descripción del empleo

This role need to base outside of United States due to regulation requirements.

My client is a market-making firm.

About the Role

We are looking for a Quantitative Market Making Trader to take responsibility for the live operation, data analysis, and optimization of market-making strategies across digital asset spot and derivatives markets.

This role combines live strategy execution and monitoring with quantitative research. You will be directly involved in the continuous development and iteration of high-frequency market-making strategies, using data-driven analysis to improve trading logic, strategy profitability, and overall market competitiveness.

Responsibilities

• Operate and monitor high-frequency market-making strategies on a daily basis, continuously tracking strategy performance and risk metrics to ensure stable and reliable production trading.
• Quickly identify and resolve trading issues, including market data anomalies, order issues, execution anomalies, and risk-control events.
• Continuously monitor live strategy performance, analyze changes in trading results, and drive improvements and issue resolution.
• Work closely with the engineering team to deploy new strategies, iterate existing versions, and continuously improve the trading system.
• Strategy Research and Optimization
• Analyze order book, trade, and order flow data to continuously improve market-making strategies.
• Study market microstructure and optimize quote placement, order cancellation logic, inventory management, and risk controls.
• Use both historical and live trading data to continuously improve key strategy metrics, including PnL and quote lifetime.
• Adjust strategy parameters according to different market conditions to reduce losses caused by adverse selection.
• Continuously research new trading signals, execution logic, and strategy improvements to enhance the overall competitiveness of market-making strategies.

Requirements

Basic Qualifications

• Bachelor's degree or above in Computer Science, Mathematics, Statistics, Financial Engineering, or a related field.
• Strong understanding of digital asset spot and derivatives markets and their trading mechanisms.
• Strong understanding of order books, matching engines, and market microstructure.
• Proficiency in Python for data analysis, strategy validation, and development of analytical and automation tools.
• Familiarity with Linux, SQL, Git, and related development tools.
• Strong data analysis skills, with the ability to identify issues from trading data and develop practical, actionable solutions.
• Strong analytical and logical thinking, with a continuous improvement mindset.

Preferred Qualifications

Candidates with any of the following experience or skills will be preferred:

• Experience in digital asset market making, high-frequency trading, quantitative trading, or exchange-based quantitative trading teams.
• Proficiency in C++.
• Experience with event-driven trading systems and low-latency trading architectures.
• Research or practical experience in any of the following areas:
• Inventory management for market-making strategies
• Fill probability modeling
• Toxic order flow analysis
• Market microstructure research

What We Look For

• Ability to independently analyze changes in strategy performance and identify the underlying causes of PnL deterioration.
• Ability to continuously optimize quoting logic, order cancellation logic, and inventory management through data-driven analysis.
• Ability to identify issues in live trading, propose improvements, and drive them through to implementation.
• Strong interest in high-frequency trading, market microstructure, and quantitative market making, with a willingness to continuously learn and conduct research.
• Strong sense of ownership and responsibility, with the ability to respond quickly to and resolve issues in a production trading environment.

If you are interested in continuously improving high-frequency market-making strategies rather than simply maintaining them, and if you enjoy using data to improve trading performance and working closely with strong engineering and trading teams to build competitive market-making strategies, we would love to hear from you.