Quant researcher - Deep learning / Machine learning - Multi-strategy Hedge Fund

Selby Jennings; Hong Kong; On-site; HKD 600,000 - 1,200,000; Full time

Job summary

Selby Jennings partners with a leading global investment firm to hire a Quantitative Researcher focused on applying deep learning and machine learning to systematic investment research. The role can be based in Hong Kong, Shanghai or Singapore, offering exposure to large-scale financial data and cutting-edge research pipelines.

You will develop ML and DL models, own the research lifecycle from idea to production, work with large datasets, evaluate models with rigorous out-of-sample tests, and

Qualifications

• Advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related field.
• Strong foundation in machine learning, statistics, optimization, and deep learning.
• Proficiency in Python and frameworks such as PyTorch or TensorFlow.
• Experience training and evaluating models at scale.
• Quantitative finance experience is preferred but not essential for candidates with strong applied AI research experience.

Responsibilities

• Develop machine learning and deep learning models to identify predictive patterns in financial data.
• Own the research process from idea generation and model development through validation and implementation.
• Work with large-scale datasets and build robust, reproducible research pipelines.
• Evaluate model performance using rigorous out-of-sample testing and statistical analysis.
• Collaborate with researchers and engineers to integrate models into production.

Skills

Machine learning

Deep learning

Python

Data analysis

Model evaluation

Education

Advanced degree in CS/Math/Stats/Eng

Tools

PyTorch

TensorFlow

scikit-learn

Job description

We are partnering with a leading global investment firm to hire a Quantitative Researcher focused on applying deep learning and machine learning to systematic investment research. The position could be based in Hong Kong, Shanghai or Singapore.

Key responsibilities:

• Develop machine learning and deep learning models to identify predictive patterns in financial data
• Own the research process from idea generation and model development through validation and implementation
• Work with large-scale datasets and build robust, reproducible research pipelines
• Evaluate model performance using rigorous out-of-sample testing and statistical analysis
• Collaborate with researchers and engineers to integrate models into production

Requirements:

• Advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related field
• Strong foundation in machine learning, statistics, optimization, and deep learning
• Proficiency in Python and frameworks such as PyTorch or TensorFlow
• Experience training and evaluating models at scale
• Quantitative finance experience is preferred but not essential for candidates with strong applied AI research experience