Analyst, Quant Research
Core
Quantitative equity researcher executing portfolio rebalances, generating trade lists, and developing systematic investment signals using machine learning and NLP.
Role type
Junior Quantitative Researcher (Systematic Active Equity)
Builds
Systematic equity signals, trade lists, and portfolio construction tools for institutional investors.
Domain
Asset Management / Quantitative Finance / Machine Learning
Deliverable
production ML models | product features
Required skills
Statistical and machine learning methodologies, Python (Pandas, NumPy), SQL, Scikit-Learn, XGBoost/LightGBM, TensorFlow, PyTorch, Financial economics, Portfolio construction theory, Natural language processing (NLP), Large language model (LLM) pipelines
Preferred skills
Experience with Unix-based systems, AWS (EC2, EMR, S3), Hadoop, Data transfer protocols (FTP/SFTP), Academic research, Fine-tuning LLMs, Prompt engineering, Retrieval-augmented generation (RAG)
Technologies
Python, SQL, Pandas, NumPy, Scikit-Learn, XGBoost, LightGBM, TensorFlow, PyTorch, AWS, Hadoop, Unix
Responsibilities
Execute portfolio rebalances and generate trade lists aligned with model views, Conduct performance attribution to assess signal effectiveness, Enhance model design and portfolio construction through systematic research, Identify and monitor key factor exposures and event risks, Advance proprietary analytics tools by creating visualizations and automating workflows, Lead the development and deployment of systematic equity signals, Apply machine learning frameworks to scale feature discovery and selection, Implement state-of-the-art NLP techniques and LLM workflows across unstructured text data
Seniority
Junior (0–2 years experience)