Quantitative Research Analyst

JEG Search LLC is a company involved in talent acquisition, specializing in connecting professionals with opportunities in various fields, including quantitative finance and technology.

Introduction

As a Quantitative Research Analyst, you will work at the intersection of quantitative finance, data, and machine learning. You will design, prototype, and productionization models — both machine learning and classical statistical/financial — that power the research delivered to subscribers. You’ll partner with senior quantitative analysts to take ideas from hypothesis to backtest to publication-ready research.

Responsibilities

• Design, prototype, and productionize machine learning and classical statistical/financial models.
• Partner with senior quantitative analysts to develop research from hypothesis to publication.

Requirements

• Bachelor’s degree in Computer Science, Mathematics, Quantitative Finance, Physics, Engineering, Financial Engineering, Statistics, or a similar discipline.
• 3–5 years of relevant work experience in quantitative finance, data analytics and modeling, or related fields.
• Hands-on experience building, validating, and deploying both machine learning models (e.g., scikit-learn, XGBoost, PyTorch or TensorFlow) and classical statistical/econometric models (e.g., statsmodels, time-series methods), with the judgment to choose the right tool for the problem.
• Strong programming skills in Python, including pandas, NumPy, and the scientific stack; comfort writing modular, testable code and using Git.
• Proficiency with SQL and relational databases (PostgreSQL preferred), including complex joins, window functions, and query performance tuning. Experience designing or contributing to data staging and transformation workflows.
• Experience working with financial time-series data and an understanding of common pitfalls (look-ahead bias, survivorship bias, regime changes).
• Familiarity with backtesting frameworks and standard performance/risk metrics (Sharpe, drawdown, turnover, etc.).
• Familiarity with quantitative finance concepts and financial instruments.
• Working knowledge of financial statements and fundamental data sufficient to incorporate them as model features.
• Excellent communication skills and the ability to collaborate effectively within a dynamic team.

Nice to Have

• Exposure to cloud data infrastructure on AWS.
• Strong academic or professional background in quantitative finance.