Quantitative Developer / Research Engineering Roles

The Phoenix Group; United States; Hybrid; USD 150,000 - 300,000; Full time

Job summary

A financial services firm is seeking a mid-senior level Quantitative Developer to build and maintain systems for strategy development and live trading. The ideal candidate will have robust software engineering experience in Python, C++, or Java, and thrive in quantitative, data-driven environments. The position offers a hybrid work model based in New York City with a competitive salary range of approximately $150,000 to $300,000 per year.

Qualifications

• Strong software engineering experience using Python, C++, Java or similar languages.
• Experience in quantitative, data‑intensive, or research‑driven environments.
• Comfort with large datasets, numerical libraries, and performance sensitive code.

Responsibilities

• Building and maintaining research and production systems for strategy development.
• Working with quants and researchers to translate models into production‑ready code.
• Developing data pipelines to support historical analysis and experimentation.

Skills

Strong software engineering experience with Python, C++, Java

Experience in quantitative, data‑intensive environments

Comfort with large datasets and numerical libraries

Familiarity with Linux‑based environments

Disciplined approach to testing and validation

Job description

Quantitative Developer / Research Engineering Roles

Location: New York City (Hybrid or Flexible)

Base pay range: $150,000.00/yr - $300,000.00/yr

What These Roles Typically Involve

• Building and maintaining research and production systems used for strategy development, simulation, and live trading.
• Working closely with quants, researchers, and portfolio managers to translate models into scalable, production‑ready code.
• Developing data pipelines and tooling to support large‑scale historical analysis and experimentation.
• Improving performance, reliability, and correctness of critical systems.
• Contributing to system architecture decisions that impact research velocity and production stability.

Experience That Tends to Translate Well

• Strong software engineering experience using Python, C++, Java, or similar languages.
• Experience working in quantitative, data‑intensive, or research‑driven environments.
• Comfort working with large datasets, numerical libraries, and performance‑sensitive code.
• Familiarity with Linux‑based environments and modern development workflows.
• A disciplined approach to testing, validation, and production readiness.

Backgrounds We Commonly See

• Hedge funds, asset managers, or proprietary trading firms.
• Quantitative research teams within financial services organizations.
• Engineering teams supporting analytics, modeling, or decision systems.
• Hybrid profiles that combine strong engineering fundamentals with applied quantitative work.

What Differentiates These Environments

Across these teams, quantitative engineering is central to the business. Developers and research engineers are expected to work close to the problem, understand the assumptions behind the models, and build systems that can be trusted in production. Ownership, technical rigor, and collaboration with senior stakeholders are core expectations.

Compensation

Compensation varies by organization and scope, but typically reflects the seniority, specialization, and business impact of the role.

How to Start a Conversation

If this type of quantitative or research‑focused engineering work aligns with your background or where you want to take your career next, you are welcome to apply or reach out directly to start a conversation. We are happy to share more context around specific teams and environments during an initial discussion.

Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Engineering and Information Technology

Industries

Financial Services, Investment Banking, and Capital Markets