Quantitative Researcher

Goliath Partners Inc.; New York (NY); On-site; USD 250,000 - 600,000; Full time

Benefits offered by this job

Autonomy

High compute resources

Direct impact on real-world outcomes

Job summary

Goliath Partners Inc. is seeking exceptional PhD-level computer scientists and ML researchers to join a small, high-caliber team in New York.

You will apply rigorous research to problems with immediate market impact, building advanced models and solutions that span from exploration to production. The role emphasizes deep technical depth, strong CS foundations, and the ability to work on problems at the intersection of computer science, ML, statistics, optimization, and financial markets.

Qualifications

• PhD in a technical field with strong academic/research background
• Unusually deep technical expertise with rigorous research track record
• Excellent Python and/or C++ programming ability
• No prior finance experience required

Responsibilities

• Research and build sophisticated quantitative models
• Develop novel approaches to prediction and optimization
• Manage full research lifecycle from exploration to production
• Collaborate across teams to apply research to markets

Skills

Python

C++

ML research

Optimization

Algorithms

Publications

Open-source contributions

Education

PhD in Computer Science/ML/Math/Physics

Tools

Git

Linux

PyTorch/TensorFlow

Job description

We’re partnering with a highly selective quantitative investment firm looking to add exceptional technical researchers to a small, high-caliber team.

This is not a traditional finance hire. The team is particularly interested in PhD-level Computer Scientists, Machine Learning Researchers, and mathematically rigorous engineers who want to apply their research ability to problems where performance has immediate, measurable impact.

What You’ll Work On

You’ll research and build sophisticated quantitative models, develop novel approaches to prediction and optimization, and work across the full research lifecycle — from first-principles exploration and experimentation through implementation and production.

The problems sit at the intersection of computer science, machine learning, statistics, optimization, and financial markets.

Who We're Looking For

The strongest candidates will typically have:

• PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, Physics, EECS, or a closely related technical field
• Exceptional academic/research background with evidence of unusual technical depth
• Strong preference for a core Computer Science foundation
• Deep expertise in algorithms, machine learning, optimization, statistics, or computational methods
• Excellent Python and/or C++ programming ability
• Track record of solving technically difficult, open-ended problems
• Publications at leading research venues, significant open-source contributions, competitive programming, or other evidence of exceptional technical ability is highly valued
• No prior finance experience required

We’re especially interested in researchers who have spent their careers around exceptionally strong technical environments and are now curious what happens when that level of research rigor is applied to markets.

Why Consider It?

You’ll work alongside an unusually concentrated group of researchers and engineers, with significant autonomy, substantial compute and data resources, and a direct connection between the quality of your research and real-world outcomes.

For the right person, compensation can reach thehigh six figures, with significant upside tied to individual and firm performance.

If your background is unconventional but technically exceptional, we still want to hear from you.