Quantitative Trading Internship
Quantitative Trading Interns will analyze market data, develop trading strategies, and build tools for trading decisions and risk management. Candidates should be STEM students graduating between December 2027 and June 2028 with strong programming, quantitative, and analytical skills.
About the job
Responsibilities
- Complete immersive training in kdb+/q, market microstructure, and trading strategy development.
- Analyze and model trading opportunities using real-world data.
- Build and enhance tools that support trading decisions and risk management.
- Collaborate with traders and technologists on complex problems.
- Present work to senior leaders and incorporate feedback.
Requirements
- Currently pursuing a bachelor's, master's, or PhD in financial engineering, applied mathematics, computer science, physics, statistics, or another STEM field.
- Expected graduation between December 2027 and June 2028.
- Strong programming skills in Python or similar languages.
- Knowledge of statistics, probability, and optimization.
- Exposure to data analysis tools such as R, MATLAB, Pandas, or NumPy.
- Interest in financial markets, algorithmic trading, and market microstructure.
- Strong critical-thinking and communication skills.
Nice-to-haves
- Experience with kdb+/q, SQL, or other database technologies.
- Participation in trading competitions, math contests, competitive gaming, or poker.
- Familiarity with machine learning techniques, including regression, neural networks, or support vector machines.
Compensation
- Hourly rate: $55–$65 per hour.
- Ten-week internship beginning in June 2027.
Skills
Python, Kdb+/Q, Market Microstructure, Algorithmic Trading, Statistics, Probability, Optimization, R, MATLAB, pandas, NumPy, SQL, Machine Learning, Neural Networks, Support Vector Machines
Similar jobs
Data Science jobs
Notion
San Francisco, CA
Analyzes product and business data, develops metrics and dashboards, and communicates actionable recommendations to cross-functional teams and leadership. Candidates should be pursuing a quantitative bachelor's or master's degree, with SQL proficiency and familiarity with Python or R.
Lyft
San Francisco, CAData Science Interns develop optimization, machine learning, and statistical models, analyze marketplace data, and run experiments in collaboration with engineering and product teams. Applicants must be pursuing a master’s or PhD and have Python experience.
Lyft
Seattle, WA
The Data Scientist develops statistical, machine learning, and optimization models, analyzes experiments and observational data, and partners with engineering and product teams to deploy algorithms and guide launch decisions. Requires a master’s degree and at least two years of relevant experience.
Socure
San Francisco, CAData Scientist II developing graph-based algorithms, entity-resolution models, and large-scale data pipelines for identity and deceased-monitoring products. Requires advanced academic training or equivalent experience, strong Python/Scala and SQL skills, and hands-on Spark and AWS experience.
Forge
San Francisco, CA
Analyzes proprietary private-market transaction and pricing data to identify valuation, liquidity, and investor trends, then translates findings into research publications and investor-facing thought leadership. Requires a bachelor's degree, strong quantitative skills, Excel and Python proficiency, and 3–7 years of relevant experience.