Researcher

Goliath Partners Inc.; New York (NY); On-site; USD 160,000 - 230,000; Full time

Job summary

Goliath Partners Inc. in New York is seeking a Machine Learning Researcher focused on systematic equities. You will join a collaborative team applying advanced ML to financial markets, with access to substantial data, compute, and engineering resources.

The role offers the opportunity to take research from experimentation through to live deployment. Responsibilities include developing models to forecast equity returns, applying DL, time-series modeling, NLP, and LLMs, and exploring pre-training,

Qualifications

• Advanced degree in CS, Math, Stats, Physics, Engineering, or related field.
• Strong track record of original research with practical applications.
• Deep expertise in machine learning, with experience in sequence modeling, LLMs, reinforcement learning, or related areas.
• Strong Python skills and experience with PyTorch or JAX.

Responsibilities

• Develop models to forecast equity returns and identify patterns in market behavior.
• Apply deep learning, time-series modeling, NLP, and LLMs to structured and unstructured data.
• Explore pre-training, fine-tuning, and reinforcement learning to extract signals from noisy, changing markets.
• Work closely with researchers, engineers, and traders to deploy scalable, robust models.

Skills

Python

Deep learning

Research experience

Education

Advanced degree (MS/PhD) in CS/Math/Stats/Physics/Engineering

Tools

PyTorch

JAX

Job description

We're partnering with an established investment firm to hire a Machine Learning Researcher focused on systematic equities.

You will join a collaborative team applying advanced ML to financial markets, with access to substantial data, compute, and engineering resources. The role offers the opportunity to take research from experimentation through to live deployment.

The role

• Develop models to forecast equity returns and identify patterns in market behavior.
• Apply deep learning, time-series modeling, NLP, and LLMs to structured and unstructured data.
• Explore pre-training, fine-tuning, and reinforcement learning to extract signals from noisy, changing markets.
• Work closely with researchers, engineers, and traders to deploy scalable, robust models.

Your background

• Advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related field.
• Strong track record of original research with practical applications.
• Deep expertise in machine learning, with experience in sequence modeling, LLMs, reinforcement learning, or related areas.
• Strong Python skills and experience with PyTorch or JAX.
• Solid mathematical and statistical foundations, alongside an interest in applying research to financial markets.

For further details, please reach out for a confidential conversation.