Global Stock Selection Researcher – Alternative Data
Core
Develop new alpha signals and improve investment strategies using quantitative analysis, alternative data, and machine learning for global stock selection.
Role type
Quantitative researcher (alternative data)
Builds
Proprietary research system features and new alpha signals
Domain
Asset management / Quantitative finance
Deliverable
production ML models
Required skills
Python, machine learning (scikit-learn, TensorFlow, PyTorch), statistical analysis, data manipulation, mathematical modeling, economic intuition
Preferred skills
Generative AI application, PhD, alternative data research experience, trading cost modeling
Technologies
Python, scikit-learn, TensorFlow, PyTorch
Responsibilities
Perform statistical and economic research using traditional and alternative data; build, train, and fine-tune machine learning architectures; add features to proprietary research systems; conduct research on implementation aspects like trading cost models and portfolio construction.
Seniority
Junior to Mid-level, hands-on IC