Fully Funded ML Research Fellow for Quant Finance

Trading Interview; Northern (KY); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Fully funded fellowship

Collaborative research environment

Access to large datasets

Job summary

Susquehanna is launching a 12-18 month fully funded faculty fellowship to pursue advanced machine learning research in a fast-paced, real-world environment, collaborating with teams at the frontier of quantitative trading.

The role focuses on developing novel ML techniques, leveraging large financial datasets, and translating insights into production-scale systems while growing the research community through collaborations and sabbatical-style engagements.

Qualifications

• Exceptional faculty with a strong ML/academic background.
• Newly minted PhDs or postdocs developing a research agenda.
• Solid theoretical ML foundation with a track record of solving practical problems.
• Strong programming skills in Python; experience with ML frameworks.

Responsibilities

• Conduct applied ML research using large-scale financial datasets.
• Develop novel modeling techniques for quantitative finance.
• Collaborate with researchers and engineers to productionize insights.
• Contribute to robust, high-performance ML infrastructure.
• Explore research directions with flexibility in scope and duration.
• Publish technical research papers in collaboration with hosts.

Skills

Machine learning

Deep learning

LLM

Statistics

Applied mathematics

Physics

Python programming

Education

PhD in ML/CS/Statistics

Postdoctoral fellowship

Tools

PyTorch

TensorFlow

Jax

Job description

Susquehanna is launching a 12-18 month fully funded faculty fellowship to pursue advanced machine learning research in a fast-paced, real-world environment, collaborating with teams at the frontier of quantitative trading.

The role focuses on developing novel ML techniques, leveraging large financial datasets, and translating insights into production-scale systems while growing the research community through collaborations and sabbatical-style engagements.