Quantitative Researcher: Build Backtested Systematic Strategies

Prime Recruitment Partners; New York (NY); On-site; USD 140,000 - 230,000; Full time

Job summary

Prime Recruitment Partners is recruiting for a top-tier systematic investment firm seeking quantitative researchers at all levels to strengthen a team regarded as among the best in the industry.

Responsibilities include building predictive models, backtesting strategies, and collaborating with engineers to productionize research—powered by Python, C++, or Java—across multiple asset classes and data sets.

Qualifications

• Strong quantitative background in Mathematics, Physics, Statistics, Computer Science, Engineering, or a related field.
• Proficiency in Python, C++, Java, or equivalent; ability to write clean, production-quality code.
• Experience working with real-world datasets and independently driving research to completion.
• Sharp analytical instincts, intellectual curiosity, and the ability to communicate complex ideas with clarity.
• Open to exceptional new graduates through experienced researchers - pedigree matters less than ability.

Responsibilities

• Build and backtest predictive models powering systematic strategies across multiple asset classes.
• Apply machine learning and statistical techniques to large, complex datasets to identify durable signals.
• Design experiments, test hypotheses, and drive ideas from concept to production.
• Collaborate closely with world-class engineers and researchers in a highly intellectually rigorous environment.

Skills

Strong quantitative background

Python expertise

C++/Java production code

Data analysis

Excellent communication

Tools

Python

C++

Java

Job description

Prime Recruitment Partners is recruiting for a top-tier systematic investment firm seeking quantitative researchers at all levels to strengthen a team regarded as among the best in the industry.

Responsibilities include building predictive models, backtesting strategies, and collaborating with engineers to productionize research—powered by Python, C++, or Java—across multiple asset classes and data sets.