Quant trader

iCIMS Middleware Test Company; Washington (District of Columbia); On-site; USD 180,000 - 240,000; Full time

Job summary

iCIMS Middleware Test Company seeks a highly analytical Quantitative Trader to develop, test, and execute systematic trading strategies across global markets. You will combine quantitative research, market intuition, and technology to identify alpha opportunities, optimize execution, and manage risk in real time.

The role requires strong Python skills and proficiency in at least one of C++/Java, with experience in backtesting, market microstructure, and multi-asset markets.

Qualifications

• Advanced degree in a quantitative field or equivalent experience.
• Strong background in probability, statistics, time-series analysis, and optimization.
• Proficient in Python; strong coding skills in C++/Java.
• Experience with backtesting and market microstructure concepts.
• Understanding of derivatives, equities, futures, FX, or fixed income markets.

Responsibilities

• Research and develop quantitative trading strategies using statistical and machine learning techniques.
• Analyze large market datasets to identify patterns and inefficiencies.
• Build and refine signal generation, portfolio construction, and position-sizing models.
• Execute trades and monitor live strategy performance, slippage, and PnL.
• Partner with quant researchers and developers to productionize strategies.
• Continuously improve execution quality and transaction cost models.
• Perform backtesting and forward testing with robust validation controls.
• Monitor risk limits and ensure compliance with trading and regulatory requirements.
• Investigate strategy drawdowns and implement corrective actions quickly.
• Produce clear performance reports and communicate insights to stakeholders.

Skills

Python

C++/Java

Statistics

Time-series analysis

Education

Bachelor’s/Master’s/PhD in quantitative field

Tools

Backtesting frameworks

kdb+/q

SQL

Linux

Job description

We are looking for a highly analytical Quantitative Trader to develop, test, and execute systematic trading strategies across global markets. The role combines quantitative research, market intuition, and technology to identify alpha opportunities, optimize execution, and manage risk in real time.

Key Responsibilities:

• Research and develop quantitative trading strategies using statistical and machine learning techniques.
• Analyze large market datasets (tick, order book, historical pricing, alternative data) to identify patterns and inefficiencies.
• Build and refine signal generation, portfolio construction, and position-sizing models.
• Execute trades and monitor live strategy performance, slippage, and PnL.
• Partner with quant researchers and developers to productionize strategies.
• Continuously improve execution quality and transaction cost models.
• Perform backtesting and forward testing with robust validation controls.
• Monitor risk limits and ensure compliance with trading and regulatory requirements.
• Investigate strategy drawdowns and implement corrective actions quickly.
• Produce clear performance reports and communicate insights to stakeholders.

Required Qualifications:

• Bachelor’s/Master’s/PhD in Mathematics, Statistics, Physics, Computer Science, Engineering, Finance, or related quantitative field.
• Strong background in probability, statistics, time-series analysis, and optimization.
• Proficiency in Python; strong coding skills in at least one of C++/Java.
• Experience with backtesting frameworks and market microstructure concepts.
• Strong understanding of derivatives, equities, futures, FX, or fixed income markets.
• Ability to make fast, data-driven decisions under pressure.

Preferred Qualifications:

• Experience in high-frequency or low-latency trading environments.
• Familiarity with machine learning for alpha modeling.
• Knowledge of cloud/distributed data infrastructure.
• Prior track record of profitable strategy development and deployment.
• Experience with kdb+/q, SQL, Linux, and real-time data pipelines.