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Quant Strategy Developer Jobs in New York (NOW HIRING)

Quant Blueprint LLC

C++ Software Engineer

Manhattan, NY · On-site

$150 - $200/hr

This role would be specifically in the Quant Strategies Group. As a quant developer of one of our world class quant trading teams, you'll have the opportunity to get exposed to all aspects of the ...

PNC

Quant & Model Development

Manhattan, NY · On-site

$109K - $202K/yr

... quantitative strategies. * Develops new model frameworks by supporting the line of business ... Conducts on-going communication with model owners and model developers during the course of the ...

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Quant Strategy Developer information

What is a quant strategy developer?

Quant Strategy Developers are professionals who design, develop, and implement quantitative trading strategies using mathematical models, statistical analysis, and programming skills. They typically work in financial institutions like hedge funds, investment banks, or proprietary trading firms. Their main role involves researching market data, building and testing trading algorithms, and collaborating with traders and other technical teams to optimize performance. They utilize programming languages such as Python, C++, or Java and have a strong background in mathematics, statistics, and finance.

What skills and qualifications are needed to thrive as a quant strategy developer?

To thrive as a Quant Strategy Developer, you need strong quantitative analysis skills, proficiency in programming (typically Python, C++, or Java), and a solid background in mathematics, statistics, or finance, often supported by an advanced degree. Familiarity with data analysis libraries, statistical modeling tools, and version control systems like Git is common, and experience with financial market data platforms is highly valued. Exceptional problem-solving abilities, attention to detail, and effective communication skills help you collaborate with traders and other stakeholders. These skills are crucial for designing robust, data-driven trading strategies that perform well in dynamic and competitive financial markets.

What are common challenges faced by quant strategy developers when collaborating with traders and other stakeholders?

Quant Strategy Developers often work closely with traders, risk managers, and other team members to translate complex quantitative models into actionable trading strategies. A common challenge is ensuring clear communication between technical and non-technical stakeholders, as well as adapting models to real-time market conditions and feedback. Balancing innovation with risk management, maintaining robust code, and quickly iterating on strategies in response to market changes are also key aspects of the role. Effective collaboration and adaptability are essential for success in this dynamic environment.

What is the difference between Quant Strategy Developer vs Quant Research Analyst?

AspectQuant Strategy DeveloperQuant Research Analyst
Required CredentialsDegree in Mathematics, Finance, or Computer Science; often requires programming skillsDegree in similar fields; strong analytical and statistical skills
Work EnvironmentDevelops trading strategies, collaborates with traders and developersConducts research, analyzes data, and tests models
Employer & Industry UsageFinancial firms, hedge funds, proprietary trading desksAsset management firms, hedge funds, financial institutions

While both roles involve quantitative analysis, the Quant Strategy Developer focuses on creating and implementing trading algorithms, whereas the Quant Research Analyst primarily conducts research and develops models to inform trading decisions. The roles often overlap but differ in their core responsibilities and focus areas.

Quant Developer - Full-time

New York, NY • On-site

Anthelion Capital Holdings
See more jobs at Anthelion Capital Holdingsexternal

$120K - $240K/yr

Full-time

Re-posted 17 days ago

Job description

About Anthelion
Anthelion Capital is an investment and data science platform. We augment our fundamental investment core with data science to make investments across the capital structure. We are building a proprietary platform that runs the full investment lifecycle, from underwriting to portfolio management.
What you'll do.
Own the quant engineering platform, end to end. You'll build and own the infrastructure our researchers and PMs depend on - the shared data layer, the backtester, the deployment path, and the monitoring that keeps live models honest. Quant developers and researchers sit side by side and write against the same systems, so what you build gets used the day you ship it.
What you'll own:
• The shared data layer - market and reference data ingestion, the feature/signal store, and the Dagster asset graph that orchestrates them, all point-in-time correct. This is the main overlap with research - you'll build it as shared, self-service infrastructure that researchers extend too.
• The backtesting and simulation engine.
• The portfolio-construction and optimization libraries PMs allocate through.
• The model deployment pipeline: promoting a model from research to production by configuration, not by rewriting.
• Monitoring and observability for live models and pipelines - the first line of defense when something drifts or breaks.
You'll also get exposure to risk-factor modeling and exposure analytics, and direct portfolio-manager support - strategy diagnostics, scenario analysis, and allocation questions.
We're looking for:
• New grad through experienced hires.
• Strong software engineering: Python plus at least one systems language, good design instincts, and the ability to build tooling other people depend on.
• Solid grounding in quantitative finance - you understand what a Sharpe ratio, a risk factor, a backtest, or a portfolio optimizer actually means and why it's built the way it is, not just how to implement it. This is a quant + developer role.
• Data engineering chops - pipelines, correctness under time (as-of-date / point-in-time), reliability.
• A platform mindset: repeatable, guard-railed, self-service tooling over one-off scripts.
• Nice to have: Dagster/Prefect, Azure, model-registry or feature-store experience, prior work at a quant/trading firm or a serious data platform, hands-on risk-modeling or portfolio-construction experience.
Additional Details:
Compensation: Base salary of $120,000 to $240,000 depending on experience. Eligible for performance based discretionary bonus.
Location : Onsite in Midtown, New York City at least 3 days per week.
Other : Must be authorized to work in the United States without employer visa sponsorship.

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