Internship – Quantitative Analyst

Note: Positions available for Spring 2026, Summer 2026 with flexible start / end dates

Company Overview

Seldon Capital is a hedge fund based in San Francisco. Our mission is to advance the craft of investing by integrating deep fundamental research with machine learning. We focus on forecasting boom-and-bust cycles driven by technological innovation, industry transformation, and government policy. By analyzing businesses at the core of these cycles, we seek to predict future value creation and destruction. 

Seldon's investment approach spans stocks, bonds, currencies, and commodities, deploying both long and short strategies. Our team comes from firms such as Soros Fund Management, Lone Pine Capital, Goldman Sachs, Balyasny, and Coatue.

We are looking for highly motivated and intellectually curious interns to contribute to our investment and trading process. This is a unique opportunity to gain hands-on experience in hedge fund research, data analysis, and execution while working alongside a seasoned investment team.

Internship Responsibilities

As a Quantitative Analyst Intern at Seldon Capital, you will:

• Build and test quantitative models to forecast asset returns, volatility, and regime shifts across equities, rates, FX, and commodities
• Perform statistical analysis on large, noisy financial and alternative datasets
• Develop features from raw market, macroeconomic, and company-level data
• Research and implement machine learning techniques for prediction, classification, and signal generation
• Evaluate model robustness through backtesting, cross-validation, and sensitivity analysis
• Assist in portfolio construction, risk modeling, and position sizing frameworks
• Collaborate with fundamental analysts and traders to translate economic hypotheses into quantitative signals
• Write clean, production-quality research code in Python
• Document assumptions, methodology, and results clearly for internal review

Who You Are

We are looking for candidates who demonstrate:

• Strong quantitative intuition and comfort working with probability, statistics, and linear algebra
• Genuine interest in financial markets and how data reflects real-world economic behavior
• Ability to reason rigorously about uncertainty, signal vs. noise, and model limitations
• Curiosity and independence in exploring new datasets, techniques, and hypotheses
• High technical standards for code correctness, clarity, and reproducibility
• Clear written and verbal communication skill

Technical Skills (Strongly Preferred)

• Proficiency in Python (NumPy, pandas, SciPy; scikit-learn or PyTorch a plus)
• Experience working with time series data
• Familiarity with statistical modeling, regression, and hypothesis testing
• Exposure to machine learning methods such as tree-based models, regularization, or neural networks
• Comfort working in a research-oriented codebase (Jupyter, Git, Linux environment)

Preferred Background

• Pursuing a Bachelor’s, Master’s, or PhD in Mathematics, Statistics, Computer Science, Physics, Engineering, Economics, or a closely related field
• Demonstrated excellence in quantitative coursework
• Prior experience in quantitative research, trading, data science, or applied ML is a plus
• Participation in math, statistics, or programming competitions (e.g., Kaggle, ICPC, Putnam, Olympiad-level work) is a plus
• Familiarity with financial data platforms (Bloomberg, FactSet) is helpful but not required

What We Offer

• Direct exposure to real hedge fund quantitative research and decision-making
• Opportunity to work on problems that directly impact capital allocation
• Mentorship from senior investors, quants, and traders with top-tier hedge fund backgrounds
• A high bar, intellectually honest research environment
• Potential for a full-time Quantitative Analyst role based on performance

Seldon Capital is an equal opportunity employer. We welcome applicants from diverse backgrounds and are committed to fostering an inclusive work environment.