Quantitative Researcher: Alpha Modeling & Production

Tradermath; Northern (KY); Hybrid; USD 100,000 - 140,000; Full time

Job summary

Susquehanna is seeking a Quantitative Researcher to design, validate, backtest, and implement advanced models across large datasets. You will develop robust alphas and contribute to long-term strategy improvements in a collaborative, mentorship-driven environment.

Expect to work with traders and technologists to push strategies into production, applying machine learning and statistical techniques while advancing your research career in a rigorous, dynamic setting.

Qualifications

• PhDs graduating by Summer 2026 or postdocs in quantitative fields such as mathematics, physics, statistics, electrical engineering, computer science, operations research, or economics.
• Analytical problem-solvers with excellent logical reasoning and a passion for turning data into decisions.
• Clear communicators in a fast-paced and highly collaborative environment.
• Programmers comfortable processing and analyzing large data sets in Python; experience with C++ (or another low-level language) is a plus.
• Strategic thinkers with demonstrated interests in strategic games and/or competitive activities.
• Self-motivated and quick to learn, thriving in dynamic, fast-moving environment.
• Visa sponsorship is available for this position.

Responsibilities

• Model development using probability theory, statistics, and machine learning.
• Backtest ideas with historical market data and large research clusters.
• Propose improvements or optimize existing strategies for production.

Skills

Python

C++

Data analysis

Communication

Problem solving

Education

PhD

Postdoc

Tools

Python

C++

Job description

Susquehanna is seeking a Quantitative Researcher to design, validate, backtest, and implement advanced models across large datasets. You will develop robust alphas and contribute to long-term strategy improvements in a collaborative, mentorship-driven environment.

Expect to work with traders and technologists to push strategies into production, applying machine learning and statistical techniques while advancing your research career in a rigorous, dynamic setting.