Machine Learning Researcher

Evolve Group; New York (NY); On-site; USD 130,000 - 210,000; Full time

Job summary

Evolve Group in New York is seeking a Machine Learning Researcher to apply modern ML to prediction, signal generation and investment decision-making. This research-focused role works with large, noisy datasets and requires strong methodological depth.

PhD in ML, CS, statistics, maths, physics or related fields is highly desirable; experience with deep learning, time series, NLP or RL is a plus. Finance experience is not required; candidates with ambitious research who want impact are encouraged

Qualifications

• PhD in ML or related field preferred.
• Strong research track record and ability to publish.
• Ability to work with ambiguous problems and large, noisy datasets.

Responsibilities

• Develop models for market prediction, signal generation and investment decisions.
• Experiment with large datasets to validate ideas and hypotheses.
• Bridge research findings with real-world trading and portfolio decisions.

Skills

Machine Learning

Deep Learning

Time Series

NLP

Reinforcement Learning

Optimization

Education

PhD in ML

PhD in CS

PhD in Statistics

Job description

A top-tier hedge fund is hiring a Machine Learning Researcher to apply modern ML to prediction, signal generation and investment decision-making.

This is a research-focused role working with large, noisy and commercially valuable datasets. You would be developing models that help identify patterns in markets, improve forecasts, generate signals, and support portfolio or trading decisions.

The work is broad and could involve deep learning, time series modelling, NLP, reinforcement learning, representation learning, optimisation, statistical modelling or large-scale experimentation. The key is not just building models, but finding ideas that are robust enough to survive contact with real financial data.

This is a strong fit for someone from an academic research lab, AI lab, Big Tech ML team or applied research group who wants faster feedback loops and a more direct connection between research and real-world outcomes.

You do not need finance experience. The firms are more interested in strong research ability, technical depth and the ability to work with ambiguous problems.

Good backgrounds include: PhD in ML, CS, Statistics, Maths, Physics, Engineering or

similar research experience in deep learning, NLP, RL, optimisation, time series or statistical modelling

This is best suited to someone who wants their research to sit much closer to real-world impact.