PhD Quantitative Researcher – Macro & ML Trading

Jump Trading; New York (NY); On-site; USD 200,000 - 250,000; Full time

Benefits offered by this job

Discretionary bonus eligibility

Medical, dental, and vision insurance

HSA, FSA, and Dependent Care options

Employer Paid Group Term Life and AD&D

Voluntary Life & AD&D insurance

Paid vacation plus paid holidays

Retirement plan with employer match

Paid parental leave

Wellness Programs

Job summary

Jump Trading Group seeks a PhD-level Quantitative Researcher to advance models and trading strategies in systematic macro. You will work with researchers, traders, and engineers to develop predictive models using statistics, ML, and data science on large datasets.

You’ll own projects end to end, from hypothesis to implementation, and contribute to live trading through rigorous testing and collaboration in a fast-paced, research-driven environment.

Qualifications

• Currently pursuing a PhD in Statistics, Mathematics, Physics, Machine Learning, or any highly quantitative field.
• Experience conducting an in-depth research project with real-world data.
• Ability to read, understand, and debug Python code.

Responsibilities

• Develop models and trading strategies in systematic macro.
• Own research projects end to end from hypothesis to implementation.
• Collaborate with researchers, traders, hardware and software developers to optimize models for live trading.
• Apply statistical analysis and machine learning to forecast and trading signals.

Skills

PhD in quantitative field

Statistical analysis

Python programming

Data modeling

Communication

Collaboration

Experiment design

ML research

Education

PhD in Statistics/Math/Physics/ML

Tools

Python

Job description

Jump Trading Group seeks a PhD-level Quantitative Researcher to advance models and trading strategies in systematic macro. You will work with researchers, traders, and engineers to develop predictive models using statistics, ML, and data science on large datasets.

You’ll own projects end to end, from hypothesis to implementation, and contribute to live trading through rigorous testing and collaboration in a fast-paced, research-driven environment.