New Grad Full-Time Quantitative Developer at WallStreetQuants

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

27 Sep, 26

Salary

0.0

Posted On

29 Jun, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, C++, Java, C#, Go, Rust, JavaScript, TypeScript, Algorithms, Data Structures, Systems Programming, SQL, Linux, Git, Quantitative Analysis, Software Engineering

Industry

Education

Description

About the Role An NYC based proprietary trading firm is seeking a motivated and intellectually curious New Grad Quantitative Developer to join the team full time. This role is designed for recent graduates from all degree backgrounds who have strong programming skills, analytical ability, and an interest in building technology for financial markets. As a Quantitative Developer, you will work at the intersection of software engineering, quantitative research, and trading. You will help design, build, and improve the systems, tools, and infrastructure that support data analysis, trading strategies, risk management, and real-time decision-making. This is an excellent opportunity for a new graduate who enjoys solving complex problems, writing high-quality code, learning quickly, and working in a fast-paced, collaborative environment. Responsibilities Design, develop, test, and maintain software tools used by traders, researchers, and engineers. Build systems for market data processing, strategy research, simulation, backtesting, and trade execution. Work with large datasets to support quantitative analysis and trading decisions. Collaborate with quantitative researchers and traders to translate ideas into reliable production systems. Improve the performance, scalability, reliability, and usability of internal platforms. Develop dashboards, analytics tools, APIs, and automation workflows. Debug and optimize code used in research and trading environments. Learn about financial markets, trading workflows, market data, and risk management. Contribute to code reviews, technical design discussions, and engineering best practices. Qualifications Recent graduate or upcoming graduate from a Bachelor’s, Master’s, PhD, or equivalent program. Open to candidates from all degree disciplines. Strong programming ability in at least one language such as Python, C++, Java, C#, Go, Rust, or JavaScript/TypeScript. Solid problem-solving, analytical, and logical reasoning skills. Ability to learn new technologies, tools, and financial concepts quickly. Strong attention to detail and commitment to writing clean, reliable, and maintainable code. Effective communication skills and the ability to work well in a collaborative team environment. Interest in financial markets, quantitative systems, trading technology, or data-driven decision-making. Preferred Qualifications Experience with algorithms, data structures, systems programming, databases, distributed systems, or cloud infrastructure. Coursework, projects, internships, or independent work involving software engineering, data science, machine learning, statistics, simulations, or quantitative analysis. Familiarity with Linux, Git, SQL, APIs, or real-time systems. Experience working with large datasets, time-series data, or performance-sensitive applications. Participation in programming competitions, hackathons, open-source projects, research projects, or technical clubs. Exposure to financial instruments, trading systems, market data, or risk analytics is helpful but not required. What We Offer Full-time role designed for new graduates. Training and mentorship from experienced engineers, traders, and quantitative researchers. Opportunity to work on impactful systems used in real-time trading and research. Exposure to financial markets, quantitative strategy development, and trading infrastructure. A collaborative, intellectually rigorous environment where strong ideas are valued. Early ownership of meaningful technical projects. Competitive compensation and benefits.

Responsibilities

Design and maintain software tools for market data processing, strategy research, and trade execution. Collaborate with researchers and traders to translate quantitative ideas into reliable production systems.