---
title: 'Quantitative Researcher at Engineers Gate'
canonical: 'https://feeny.ai/job/quantitative-researcher-engineers-gate-hong-kong-qfjnzrvphkmp'
type: 'job'
last_seen: '2026-09-08'
---

# Quantitative Researcher at Engineers Gate

- **Company:** Engineers Gate
- **Location:** Hong Kong
- **Posted:** 2026-05-20
- **Last confirmed live:** 2026-09-08
- **Apply:** https://job-boards.greenhouse.io/engineersgate/jobs/7946534

## Job description

## About EG

Engineers Gate (EG) is a leading investment manager founded in 2014 as a quantitative, computer-driven trading firm. Today, EG operates as a diversified, multi-strategy investment platform that combines systematic research with selective discretionary approaches.

EG's multi-manager platform allows independent investment teams to pursue distinct strategies while benefiting from shared infrastructure, risk management, and operational support. The firm’s collaborative groups of researchers, engineers, and investment professionals deploy sophisticated statistical models, proprietary technology, and a centralized data platform to isolate and solve challenging problem sets in the global financial markets.

## About The Role

We are seeking a motivated Quantitative Researcher to join one of our systematic equity trading teams. In this role, you will leverage the team’s existing research and trading infrastructure to research, develop, and support systematic equity strategies across the full trading lifecycle, from alpha research and signal generation to portfolio construction, execution, and ongoing risk management.

The ideal candidate has a strong quantitative foundation, hands-on experience with systematic equity strategies, and an interest in translating research into live trading. This individual will work closely with the Portfolio Manager within a collaborative, fast-paced environment.

## Key Responsibilities

- Clean, validate, and analyze large-scale raw datasets to build a reliable foundation for US and China equities alpha research
- Assist Portfolio Managers in developing tools to analyze, optimize, and monitor portfolio performance
- Apply statistical and machine learning techniques, including deep learning models where appropriate, to enhance signal generation and forecasting
- Contribute across the full trading lifecycle: ideation, research, backtesting, optimization, deployment, and live performance monitoring
- Stay informed on equity market structure, short-horizon dynamics, emerging data sources, and relevant technological advancements across both US and China markets

## Qualifications

- MS or PhD in a quantitative field (e.g., mathematics, statistics, computer science, physics, engineering) is a plus.
- 1–5 years of experience in systematic equity research or quantitative trading.
- Strong quantitative, mathematical, and programming skills; Python required
- Working knowledge and practical experience applying machine learning models; experience with deep learning is a plus.
- Familiarity with China equity markets or cross-border trading dynamics is a plus

Please review the applicable candidate privacy notice (the “Notice”) available at https://www.eglp.com/legal-and-privacy-notices. By seeking employment with Engineers Gate HK Limited or EG SG Pte. Ltd., as applicable (“EG”) or submitting your application and/or personal data to EG, you acknowledge that you have read and understood the Notice and have agreed and consented to EG's collecting, using, disclosing, processing and/or transferring your personal data in accordance with the Notice.

## About Engineers Gate

## Company Overview
- **One-liner**: Engineers Gate is a quantitative investment company that uses computer-driven trading and advanced data science to generate superior returns in global financial markets.
- **Entity Type**: Private
- **Headquarters**: New York City, USA (with offices in Boston, London, Singapore, and Hong Kong)
- **Founded**: 2014
- **Founders**: Glenn Dubin

## Core Business
- **Primary industry/industries**: Investment Management / Quantitative Finance / Hedge Funds
- **Target customers**: Institutional investors (via private funds) and proprietary trading operations — predominantly B2B.
- **Mission or purpose statement**: “Implement scientific and mathematical methods to explore, isolate, and solve problems in the global financial markets” — with a core belief that systematic, research-driven strategies will outperform over time.

## Products & Services
- **Hedge Funds / Multi-Strategy Investment Platform**: The firm manages several private investment funds that combine systematic and selective discretionary approaches. Investment teams pursue independent strategies while leveraging shared infrastructure, risk management, and a proprietary data platform.
- **Quantitative Trading & Research**: In-house teams research and execute computer-driven strategies across equities, futures, and other asset classes, covering full trading lifecycles (alpha research, signal generation, portfolio construction, execution, risk management).

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed (private company).
- **Key Metric**: **Assets Under Management (AUM)** — approximately **US$4 billion** (as of 2025). The firm also raised an estimated **$300 million in total funding** per LinkedIn (though some sources list this as total capital raised; AUM is the more standard metric).
- **Notable Investors/Partners**: Not publicly detailed. The firm operates as a Registered Investment Advisor (SEC) and Commodity Pool Operator (CFTC), with key leadership including **CEO Greg Eisner**.
- **Growth Signals**:
  - Headcount grew **49% year-over-year** to **187 employees** (LinkedIn, 2025); Wikipedia reports 179 employees in 2025.
  - Opened an office in Singapore in May 2024, expanding Asian presence.
  - Actively hiring for quantitative researchers, engineers, and operational roles across New York, London, Hong Kong, and Singapore.

## Competitive Advantages
- **Quantitative & Technology Moat**: Deep integration of proprietary statistical models, machine learning, and a centralized data platform gives a persistent edge in signal discovery and execution.
- **Multi-Manager Model**: Allows independent investment teams to operate with autonomy while sharing best-in-class infrastructure, risk management, and operational support — attracting top talent.
- **Culture of Collaboration & Rigor**: The firm’s emphasis on open idea exchange, intellectual curiosity, and a “friendly but challenging” environment differentiates it from larger, more bureaucratic asset managers.
- **Talent Density**: Team composed of researchers, engineers, and financial professionals from top academic and industry backgrounds (e.g., math, physics, computer science, and prior quant trading experience).

## Strategic Focus
- **Multi‑Strategy Expansion**: Continuing to build a diversified platform that scales both systematic and discretionary strategies across global markets.
- **Technology & Data Leadership**: Investing in proprietary infrastructure to stay ahead of market microstructure changes and emerging data sources.
- **Talent Acquisition**: Aggressively recruiting quantitative researchers, engineers, and portfolio managers to support growth, especially in US, Europe, and Asia.
- **Risk Management & Alignment**: Maintaining a patient, disciplined approach to capital allocation with strong alignment between the firm, its investment teams, and its investors.

## Why Work Here
- **Culture**: Collaborative, intellectually curious, and open — described as “as intellectually rewarding as life in academia and as inventive and dynamic as working at a start-up technology firm.”
- **Work‑Life Balance & Benefits**: “Superb benefits” including fully covered medical, dental, and vision insurance, generous vacation and personal days. The firm also supports social and philanthropic causes.
- **Remote/Hybrid Policy**: Most roles are based in office hubs (NYC, London, Singapore, Hong Kong), though some positions (e.g., U.S.‑based telecommuting roles) allow remote work. The firm explicitly touts flexibility for certain roles.
- **Engineering & Research Environment**: Emphasis on open‑source style sharing of ideas, use of state‑of‑the‑art tools (Python, ML/DL frameworks, large‑scale data pipelines), and exposure to full trading lifecycle.

## Sources
1. [Engineers Gate – Official Site](https://www.eglp.com/)
2. [Engineers Gate – Wikipedia](https://en.wikipedia.org/wiki/Engineers_Gate)
3. [Engineers Gate – LinkedIn](https://www.linkedin.com/company/engineers-gate)
4. [Careers – Greenhouse (Open Positions)](hhttps://boards.greenhouse.io/engineersgate)
5. [Quantitative Researcher Job Posting – Greenhouse](https://job-boards.greenhouse.io/engineersgate/jobs/7946534)

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