Quantitative Research Intern

This Quantitative Researcher Intern role at Solar Digital Agro LLC is an on-site position based in Chicago, IL. The intern will support the quantitative research team in developing and evaluating systematic trading strategies, with a particular focus on intraday alpha research
, financial market analysis, and statistical modeling.

Day-to-day responsibilities include collecting, cleaning, and analyzing financial market data, researching short-term trading signals, implementing quantitative models, and conducting strategy backtesting. The intern will evaluate strategy performance using risk-adjusted return metrics, transaction costs, and market conditions.

The intern will collaborate with traders and senior researchers to test hypotheses, refine trading signals, document methodologies, and present research findings. This internship provides hands‑on exposure to quantitative trading, financial markets, and systematic investment research in a professional trading environment.

Company: Solar Digital Agro LLC

Location: Chicago, IL (On-site)

Employment Type: Internship

This Quantitative Researcher Intern role at Solar Digital Agro LLC is an on-site position based in Chicago, IL. The intern will support the quantitative research team in developing and evaluating systematic trading strategies, with a particular focus on intraday alpha research
, financial market analysis, and statistical modeling.

Day-to-day responsibilities include collecting, cleaning, and analyzing financial market data, researching short-term trading signals, implementing quantitative models, and conducting strategy backtesting. The intern will evaluate strategy performance using risk-adjusted return metrics, transaction costs, and market conditions.

The intern will collaborate with traders and senior researchers to test hypotheses, refine trading signals, document methodologies, and present research findings. This internship provides hands‑on exposure to quantitative trading, financial markets, and systematic investment research in a professional trading environment.

• Strong foundation in Statistics and Mathematics
  , including probability, statistical inference, regression analysis, and quantitative modeling.
• Demonstrated Analytical Skills and interest or experience in Quantitative Research
  , including hypothesis testing, time-series analysis, and interpretation of financial data.
• Interest or experience in Quantitative Trading and Intraday Alpha Research
  , including signal generation, strategy development, backtesting, and risk/return analysis.
• Proficiency in Python
  , including commonly used libraries such as Pandas, Num Py, Sci Py, or similar quantitative research tools.
• Familiarity with Financial Markets
  , including equities, ETFs, futures, options, or other financial instruments.
• Understanding of Strategy Performance Evaluation
  , including Sharpe ratio, drawdown, volatility, transaction costs, and potential overfitting.
• Currently pursuing or recently completed a degree in Statistics, Mathematics, Financial Engineering, Computer Science, Economics, Physics
  , or a related quantitative discipline.
• Ability to work on-site in Chicago, IL
  , collaborate effectively with researchers and traders, and communicate technical findings clearly.
• Experience with market microstructure, high-frequency data, SQL, Git, machine learning, or financial data APIs is a plus.

• Hands‑on Quantitative Research
  
  Experience:
  
  Work on real‑world research problems involving intraday trading signals, systematic strategies, and financial market data.
• Exposure to Professional Trading: Gain practical insights into trading operations, quantitative investing, market dynamics, and risk management.
• Direct
  
  Collaboration:
  
  Work closely with traders, quantitative researchers, and engineers in a collaborative, research-driven environment.
• Technical and Professional Development: Strengthen skills in Python, statistical modeling, backtesting, and quantitative strategy evaluation.
• Meaningful Research Contributions: Opportunities to develop, test, and refine quantitative research ideas with practical applications.
• Career Growth Opportunities: Gain valuable experience in quantitative finance, algorithmic trading, and financial technology.