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Quantitative Researcher | Engineers Gate (EG)

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Location: New York, NY | Work Mode: Full-time | Salary: $130,000 – $150,000 (Base) | Posting date/time : February 5, 2026


Job Description

About Engineers Gate

Engineers Gate (EG) is a leading quantitative investment company focused on computer-driven trading in global financial markets. We utilize sophisticated statistical models to identify predictive signals, providing our investment teams with a proprietary, state-of-the-art technology and data platform to optimize alpha research.

Role Summary:

We are seeking a highly motivated Quantitative Researcher to join a systematic equity trading team. You will leverage existing infrastructure to develop innovative trading strategies across the full cycle—from deep data analysis to backtesting and deployment. Reporting directly to the Portfolio Manager (PM), you will have the opportunity to influence all aspects of systematic trading.

Key Responsibilities:

  • Process and analyze diverse data sets, including both structured and unstructured formats.
  • Collaborate with the PM to develop alpha signals from traditional and alternative data sets.
  • Adopt a data-driven approach to generate creative alpha ideas and perform rigorous backtesting.
  • Improve existing research and trading infrastructure while adding new analysis and research tools.
  • Maintain a proactive approach to problem-solving and stay informed on advancements in quantitative finance and emerging technologies.

Qualifications:

  • Strong programming skills and a passion for deep-dive data analysis.
  • Ability to combine financial intuition with scientific and mathematical methods.
  • Proven ability to thrive in a fast-paced, data-driven environment.
  • High level of motivation and initiative in the pursuit of innovative trading strategies.

Job details made easy by trendtoday360

Position: Systematic Equity Quantitative Researcher
Focus: Alpha Signal Generation & Alternative Data Analysis
Core Technology: Statistical Modeling, Backtesting Engines, Unstructured Data Processing

✅ Job Summary and Focus:

This role at Engineers Gate is for a Data-First Alpha Hunter. Unlike larger firms where roles are siloed, this position offers Full-Cycle Strategy Exposure. The focus is on Alternative Data Ingestion—taking raw, unstructured information and turning it into tradable equity signals. You will act as the “engine room” for the Portfolio Manager, using sophisticated statistical models to prove or disprove financial intuitions. If you are passionate about the intersection of Scientific Computing and Global Markets, this role provides the platform to deploy strategies at the cutting edge of the industry.

📌 Key ATS Resume Keywords:

Quantitative Researcher, Engineers Gate, Systematic Trading, Alpha Generation, Alpha Signals, Equity Trading, Statistical Modeling, Backtesting, Alternative Data, Unstructured Data, Predictive Signals, Quantitative Finance, Financial Intuition, Portfolio Management, Data Analysis.

💰 Compensation and Industry Demographics:

The anticipated base salary for this role is $130,000 – $150,000. It is important to note that in the quantitative hedge fund space, performance-based bonuses often constitute a significant portion of total compensation.

In the context of the U.S. Quantitative Investment workforce for 2025-2026:

  • Racial Representation in Quant Research: According to 2025 industry labor statistics for “Quantitative Financial Researchers”:
    • White: 45.8%
    • Asian: 41.2%
    • Hispanic or Latino: 6.5%
    • Black or African American: 4.9%
  • Gender in Systematic Trading: Women currently represent approximately 19% of quantitative research roles in top-tier hedge funds. Firms like Engineers Gate increasingly emphasize continuous learning and development to foster a more inclusive and diverse high-performance culture.
  • Market Trends: The “Alternative Data” boom of 2026 has increased the demand for Quants who can process unstructured data (NLP, satellite imagery, sentiment analysis) by 22% compared to those focused solely on price-volume data.

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